Strathmore University SU+ @ Strathmore University Library Electronic Theses and Dissertations 2019 The Influence of service quality on market performance: a case of Standard Gauge Railway (SGR) freight services from a clearing agent perspective Diana I. Akivaga Strathmore Business School (SBS) Strathmore University Follow this and additional works at https://su-plus.strathmore.edu/handle/11071/10169 Recommended Citation Akivaga, D. I. (2019). The Influence of service quality on market performance: A case of Standard Gauge Railway (SGR) freight services from a clearing agent perspective [Thesis, Strathmore University]. https://su-plus.strathmore.edu/handle/11071/10169 This Thesis - Open Access is brought to you for free and open access by DSpace @Strathmore University. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of DSpace @Strathmore University. For more information, please contact librarian@strathmore.edu THE INFLUENCE OF SERVICE QUALITY ON MARKET PERFORMANCE: A CASE OF STANDARD GAUGE RAILWAY (SGR) FREIGHT SERVICES FROM A CLEARING AGENT PERSPECTIVE Diana Imali Akivaga MBA/92700/2016 A Research Proposal Submitted to the Strathmore Business School in Partial Fulfilment for the Degree of Masters in Business Administration of Strathmore University June,2019 DECLARATION I declare that this research proposal is my original work and has not been previously submitted for the award of a degree by this or any other University. To the best of my knowledge and belief, the dissertation contains no material previously published or written by another person except where due reference is made in the thesis itself. © No pat1 of this thesis may be reproduced without petmission of the author and Strathmore University. Diana lmali Akivaga June,2019 Approval The dissertation of Diana Imali Akivaga was reviewed and approved by: Dr. Nancy Njiraini (Supervisor) Strathmore Business School Dr. George Njenga Dean, Strathmore Business School Prof. Ruth Kiraka Dean, School of Graduate Studies Strathmore University II ABSTRACT The Standard Gauge Railway (SGR) is the most expensive infrastructure project Kenya has embarked on since it gained independence in 1964. The project is largely funded through debt and it is expected that revenues from the railway operations shall be used to repay the loan. One product offered on this infrastructure is SGR freight services. Market perfmmance of this product is therefore a critical success factor for the project. The objective of the study was to establish the influence of service quality on market performance of SGR freight services from a clearing agent perspective as measured through intention to buy. Data was collected from 273 clearing agents using a structured questionnaire. A modified SERVQUAL instrument was used to capture customers ' perception of service quality. The instrument futther captured information on the influence of WOM on intention to use SGR freight services and the influence that each SERVQUAL dimension has on intention to use SGR freight services. Data was then analysed using descriptive, cmTelational and inferential techniques. A factor analysis was conducted to distinguish dimensions from the customer' s perspective, Spearman's rank correlation coefficient applied to draw conclusions on the influence of WOM communication and Binary logistic regression was used to predict the probability that each service quality dimension influences market perfmmance of SGR freight services. The study revealed that there is a positive relationship between service quality and market perfmmance of SGR freight services as determined by intention to buy/ use the services. Other findings revealed that disconfirmation was negative for SGR freight services across all service quality dimensions and that there was a moderate positive relationship between WOM communication and future purchase intention for SGR freight services. Fmther, it determined two dimensions as distinguished by customers namely accessibility & effectiveness and service encounters and detetmined tangibles and responsiveness to be the largest source of influence on use of SGR freight services. The study recommended that service improvement strategies focus on these areas. This study contributes to the body of academic knowledge by providing evidence of the relationship between setvice quality and market perfmmance for SGR (train) freight services in Kenya. Key words: Service Quality, Word of Mouth, Market Performance, Standard Gauge Railway 111 TABLE OF CONTENTS DECLARATION ......................................................................................................... .................. ii ABSTRACT ................................................................................................................................ .. iii TABLE OF CONTENTS ............................................................................................................ iv LIST OF FIGURES ................................................................................................................... viii LIST OF TABLES ............................................................................................................... ... ..... ix ABBREVIATIONS AND ACRONYMS ...................................................................................... x DEFINITIONS OF KEY TERMS .............................................................................................. xi ACKNOWLEDGEMENTS ....................................................................................................... xii DEDICATION ........................................................................................... ... .............................. xiii CHAPTER ONE: INTRODUCTION .......................................................................................... ! 1.1 Background of the Study .... .... .... .. .... .. .... ........ ...................... .. ...................... .. .... ...... .. .... .. 1 1.1.1 Service Quality .................... .. .. .... .. .... .. .............................................. .. ...................... 1 1.1.2 Market Performance .. ..... ................... ........... ....... ... ... ..... .... ... ... ................. ..... ........... 3 1.1.3 Word of Mouth Communication ...................................... ........ .... .. ................ .. ......... 5 1.1.4 Overview of Standard Gauge Railway Freight Services ...................................... .... 5 1.2 Statement of the Problem ....... .............. .... ..... .. .. ........................ ..... ............ ..................... . 6 1.3 Research Objectives ............................................................ ... ... ... ... ........................... ... ... 8 1.3.1 General Objective .. .. ........ .. ................................ .... .... ...................................... ......... 8 1.3.2 Specific Objectives ........ .... .. ............................................................ .... ... ... ... ... ......... 8 1.4 Research Questions .... ... ............................................................................................. ... ... 9 1.5 Scope of the Study ............. .. ... .... ................................. .. ... .... .......... ....... ... .... .. ..... .... ......... 9 1.6 Significance ofthe Study .................................................................. ............................... 9 CHAPTER TWO: LITERATURE REVIEW ........................................................................... ll lV 2.1 Introduction .................. .......... .. ...................................................................................... 11 2.2 Theoretical Foundation .... ... ... ........... .... ..................................... .. ........ .... ... .. .... ... ... ... ... . 11 2.2.1 Cognitive Dissonance Theory .. .. .... .. .... .. ................................................................. 11 2.2.2 Theory of Planned Behaviour .. .................................... .. ...................... .. .......... .. .. ... 13 2.3 Etnpirical Review ......................................... ....... ... ... ........ ................ .. ....................... 14 2.3.1 ServiceQuality. ...................................... .... ... ... .. .... ....................................... .. ........ 14 2.3.2 Market Performance ........ .. ....... .. ....................... .. ...... ... ... ... ... ... ... ... ...... ..... ... .... ...... . 20 2.4 Conceptual Framework .. .. ..... .... ... ...... ... ..... ... .... ..... ....................................................... . 23 2.6 Summary of Literature and Research Gaps .... .... .. .. ........ .. .... .. .... .. .... ........ ........ .... .... .. .... 24 CHAPTER THREE: RESEARCH METHODOLOGY .................... ..................... ................. 26 3 .1 Introduction .................................... ............................ .. ... .......... .. .... ... ... ... ...... ...... .. ....... . 26 3.2 Research Design ... ......... .. .... ... ... ... ...... .. ...................... ... ............. .. .................................. 26 3.3 Population and Sampling Frame ................................ .. .... .. .......... .. ...... .. .............. .. ...... .. 27 3.4 Sample and Sampling Technique ...................... .. .. ...... .... .. .................................. .. ........ 27 3.5 Research Instruments and Data Collection Techniques .......... .. .... .. .... .. ...... .. .... ...... .. ..... 28 3.6 Data Processing and Analysis ... .......................................... .... .... .... ... ...... .. ...... .... .......... 30 3.7 Research Quality .... .................................... ....................................... .. .............. ... ... ... ... . 31 3.7.1 Reliability .. .. .. .... .... ... ... ... ....... .. ............................................ ................................... 31 3.7.2 Validity ... ... ... ................. ............................ ... ......... ... ... ........................................... 32 3.8 Ethical considerations .. ...... ......... ..................................................... ............. ....... ... ... ... . 32 CHAPTER FOUR: DATA ANALYSIS AND PRESENTATION ........................................... 33 4.1 Introduction ................................................ ................................. ... ....... .... .. .. .... .. .... .. ..... 33 4.2 Response Rate ...................................... ............................... .. ................ .. ....................... 33 4.3 Descriptive Statistics ........................... .. ...... ... .............. .... .. ........ .. .................................. 34 4.3.1 Gender Proportions ......................................... ............................ ... ... ... ... ... ......... ... . 34 v 4.3.2 Proportion by ownership .................................................... .......... ..................... ...... 35 4.3.3 Length of operation ..................... ........................................................... ...... ........... 35 4.3 .4 Company size by number of customers served ...... .. .................. .... ......... ... ... .... ..... . 36 4.4 Overall Perception of Service Quality ........................................................................... 36 4.6 Behavioural intentions ...... ... ... ........................................................................................ 41 4.6.1 WOM Communication .................... .. ... ... ... ....................................................... ...... 42 4.6.2 Recommendation Influence ................. ..... ........... .. ... ..... .............. .. ... ... ...... ... ... ...... . 44 4.6.3 Future Purchase Behaviour ... ...... ... ... ... ... .. .... ............. .. ... ... ... .. .. .............................. 44 4.6.4 Relationship between WOM Communication and future purchase intent of SGR Freight Services .. ... ........ .... ... .... ........................................ .... .. ...... ..... .. ... ... ... .. ....................... 46 4.7 Influence of Service Quality Dimensions on Market Perf01mance of SGR freight services as determined by intention to use/buy ..... ... ........ .... ......... ... ... .. ... ..... .. ............ ... .... .. ...... ....... .. .... 4 7 4.7.1 Service Quality Dimensions likely to influence Market Performance of SGR freight services as detetmined by intention to use/buy .... ..... ...... ...... ... ......... .. ..... ................ ........ .. .... .. . 49 5.1 Introduction ................ ................ ..... .... .. .............. ........... .............. ... ............................... 51 5.2 Discussion .. ............................................................................................................. ... ... . 51 5.2.1 Overall Perception of Service Quality ofSGR freight services by clearing agents ... .... 51 5.2.2 Influence of WOM on achieving buying intention of SGR freight services .................. 52 5.2.3 Service quality dimensions most likely to influence market performance of SGR freight services as determined by buying intention .............................................................................. 53 5.3 Conclusion ... ...... ... ... ... ... ... ...... ... .... ...... .. ... ... ... ...... ... ... ..... .......... .. ................. ..... ....... ...... 54 5.4 Recommendations and Management strategies ........................... .......................... .... ... . 56 5.4.1 Managerial implications ................. .... ... .. .... .. ........................... ................ .. ... ... ...... . 56 5.4.2 Policy implications .................................................................................................. 56 5.5 Limitations ofthe study .............................. ... ~ ................................................. ........ .. ..... 57 5.6 Areas offutther research .......................................................... ............................. ..... .. .. 57 VI References ..................................................................................................................................... 58 Appendix I: Ethical Clearance ................................................................................................... 69 Appendix II: Letter of Introduction ........................................................................................... 70 Appendix III: NACOSTI Study Permit ..................................................................................... 71 Appendix IV: Questionnaire ....................................................................................................... 72 Appendix IV: List of Licensed Clearing Agents ....................................................................... 80 VII LIST OF FIGURES Figure 2.1: Theory of Planned Behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Figure 2.2: Comparison ofHofstede's cultural dimensions ...................................... 18 Figure 2.3: Antecedents to Customers Expected Service .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ... 22 Figure 2.4: Service Quality and Market Performance .. .. .. .. .. .. .. .. .. .. .... .. .... .. .. .. .. .. .. .. .. 23 Figure 4.1: Respondent distribution by gender (Percentage) ..................... ... ...... ... ..... 34 Figure 4.2: Respondent distribution by ownership (Percentage) ... ....... ........... .. . ... ... ... 35 Figure 4.3: Respondent distribution by length company has been in operation (Percentage).35 Figure 4.4: Respondent distribution by number of customers served annually (Percentage) .. 36 Figure 4.5: Scree Plot ......... ... ...... ......... .......................................................... 40 Figure 4.6: WOM communication for SGR Freight Services ...................................... 43 Figure 4.7: Recommendation Influence for SGR Freight Services ... ......... .................... 44 Figure 4.8: Future Purchase Intent for SGR Freight Services ......................................4 5 Figure 4.9: Most influential/ impmtant service quality dimensions .............. . ..... ... . ...... .48 Vlll LIST OF TABLES Table 2.1: Dimensions of Service Quality ........................................................ 16 Table3.1: Operationalisation of the Service Quality- Adapted to SGR Freight Services .. 29 Table 3.2: Reliability test results ........ ... . .. . ... ..... . ..... . ................................. .... . 31 Table 4.1: Response Rate and Completeness ... ...... ... ........ ....... ... ...... ... ...... .. ...... 33 Table 4.2: Kaiser Meyer Olkin (KMO) and Bm1lett' s Test.. .................................. . 34 Table 4.3: Service Quality Score ................................................................. .. 36 Table 4.4: Communality Index ... .. ............................. . .... . ................. ... ......... 38 Table 4.5 : Eigenvalues ... . ................................... . .................. .. ............... .. . 39 Table 4.6: Rotated Component Matrix ... . . . .. .... .. . .................................. .. ...... ... 40 Table 4.7: N arne of the two core factors ....................... . ............ . . . ...... . ........ ... . 41 Table 4.8: Behavioural intentions for SGR Freight Services .. ........ .. ... . .. .. ............... 41 Table 4.9: Future purchase intent for clearing agents using and not using SGR freight services ..... .... .. . .................................... ... ..... .... ...... .. .... ...... ...... 45 Table 4.10: Spearman's Rank Con·elation Test (WOM communication and future purchase intent) ....................................... .. . ... ... ... ... .... . . ... ... ........ . ......... 46 Table 4.11: Service Quality Dimension most likely to influence market performance of SGR freight service . ................................ ...... ................................ . ... 4 7 Table 4.12: Binary logistic regression (Service quality dimensions and market performance of SGR freight services) ............ .. .... .. .. .. ...... ... .. .... ... .. ... . .... ..... .......... 49 lX ABBREVIATIONS AND ACRONYMS COT Cognitive Dissonance Theory EDT Expectancy Disconfirmation Theory HOQ House Of Quality ICON Inland Container Depot- Nairobi KPA Kenya Potts Authority KR Kenya Railways KRA Kenya Revenue Authority SGR Standard Gauge Railway WOM Word of Mouth X DEFINITIONS OF KEY TERMS Service Quality: The extent to which a service delivered meets customers' expectations. Market Performance: Non-financial performance metrics that relies on the psychographic factors increasing reputation, preferences, satisfaction, re-buying and to achieve buying intention Standard Gauge Railway High capacity high speed railway for cargo transpmtation that connects Freight Services: Mombasa to Nairobi Word of Mouth Influence: Process where interpersonal communications between parties has the ability to influence the receiver's behaviour. Theory of Planned Predicts an individual's intention to engage in a behaviour at a specific Behaviour: time and place. XI ACKNOWLEDGEMENTS First and foremost, to the Almighty God, for the gift of life and all the blessings he has bestowed upon me and my family. To Dr. Nancy Njiraini, my supervisor for the continuous guidance, support and thought leadership provided throughout this journey. To the panellists Dr. Everlyne Makhanu and Dr. Stella Nyongesa and for their invaluable input. To my classmates for the intellectual stimulation that made this MBA experience memorable and invaluable. Last but not least, my family and friends for their inspiration, endless support and encouragement. I would particularly like to single out my husband who continuously supported and motivated me throughout this journey, my children who allowed me to take time away from them to invest in my studies, my nannies who filled in tllis gap and my mother who is my rock and inspiration. Xll DEDICATION In memory of Symonds Kichamu Akivaga 1944-2017 Who taught me that we must always seek to enhance our knowledge even if it means adding little things every day. Xlll CHAPTER ONE: INTRODUCTION Service may be defined as 'the application of specialized competences (skills and knowledge), through deeds, processes, and performances for the benefit of another entity or the entity itself' (Vargo & Lush, 2004). It is provided in almost every sector of the economy and has become an impmtant component in organisations. This is partially driven by the fact that customers are now conscious of their rights and wants and demand higher standards of service thus driving the need for organisations to maintain high levels of service quality. Fmther, when customers buy products, they do so for the benefits that these products provide them which translates to value for the customers (Gronroos, 2017). These factors are key in driving market performance in a firm. While this concept applies to both public and private sector organisations, it has not taken root as firmly in public sector organisations as it has in private sector organisations (Rishel, Glover, & Niems, 2018). 1.1 Background of the Study 1.1.1 Service Quality Service quality has been defined by various scholars. Cronin and Taylor (1992) define it as a measure of the extent to which service delivered meets customers' expectations. Ghobadian, Speller and Jones (1994) highlight that service quality is detetmined by customers' perception. This is consistent with Gronroos (1984) who state that it is the outcome of an evaluation process where a customer compares his expectations with the service they perceive they have received. Lehtinen and Lehtinen (1982) instead use three quality dimensions: physical, corporate which includes the company's image and interactive which refers to interactions between the organisations staff and customers as well as among customers themselves. Dubinsky (2015) highlights that quality is perceived in the moment(s) where the customer interacts with the service provider. These viewpoints are generally corraborated by Sachdev and Verma (2004) who argue that there are two perspectives of quality measurement: intemal and extemal. The intemal perspective focuses on intemal efficiencies through the doing it right the first time confmmance 1 mantra and the extemal perspective focuses on customer perception and satisfaction. It is this extemal perspective that can be described as service quality which this study focused on. According to Gronroos, 1984, ' the quality of the service is dependent on two variables: expected service and perceived service. Therefore, in a service quality model we need to know the resources and activities, under the control and outside the immediate control of the fitm that have an impact on these variables ' . Pg. 37 Service quality models thus take into account various factors that could influence these variables including promises vs. perfmmance, technical quality and functional quality. Services offered by most organisations contain both tangible and intangible pmts in different proportions. Only pat1 of the service production process is visible and it is these activities that customers experience and evaluate in every detail. The invisible parts can only be experienced (Bei & Chiao, 2001 ; Gronroos, 1984). The consumer thus perceives what they receive as an outcome of the process (tangible) as well as how the process functions and their interactions with the organisation (intangible). These result in the technical and functional features of services from which a model of how quality of services are perceived and evaluated by customers can be derived (Gronroos, 1984; 2001 ). Service quality dimensions are therefore those attributes that are impmtant to the customer thereby contributing to their expectations and perceptions of service. Knowing and measuring these dimensions gives organisations insights into effective ways of improving service quality. Since service quality problems are not always visible to the service provider, managing perceived service quality is done by managing gaps between customers' expectations and their perception of the service they actually received (Rowley, 1998). Managing service quality in the public sector is generally more complex than doing the same in private sector (Donnelly, 1999). Literature identifies several reasons for this; public sector organisations are responsible and accountable to citizens, communities as well as to its customers (Ramseook-Munhurrun & Lukea-Bhiwajee, 201 0), futther they involve allocating resources and publicly justifying and accounting for what has been done [Gowan et al. (2001) as cited by Ramseook-Munhunun & Lukea-Bhiwajee (2010)]. Complexities of partnership arrangements for the design and delivery of services, unclear perfmmance targets, a culture of lack of 2 experimentation, slow adaptation to change and emphasis on shmt term gains are other reasons that complicate the management of service quality in public organisations (Brysland & Curry, 2001). The Service Quality definition that was adopted for this study is the extent to which a service delivered meets customers' expectations by Cronin and Taylor (1992). This was measured as Perception of delivered service (Outcome)- Customer Expectations. 1.1.2 Market Performance The performance of a firm can be measured through sales revenue, market share, profitability, competitive advantage, customer satisfaction and loyalty (Jayapal & Omar, 2017). Gao (201 0) introduces a new integrated model for measuring marketing performance comprising customer satisfaction, market share, brand equity, innovation and customer loyalty. Gaal (2008) presents an approach to market performance measurement that relies on psychographic factors such as increasing reputation, preferences, satisfaction, re-buying and to achieve buying intention. A firm ' s competitiveness can be measured in financial or marketing terms. In marketing tenns, there are key measures which link directly to functional areas of the business such as product perfonnance, service performance and customer value (Riley, 2019). Such non-financial metrics have gained popularity as tools for measuring performance (Ellis & Curtis, 1995). The service sector encompasses a diverse range of organisations including governmental organisations, not for profit organisations and for profit organisations (Ghobadian et al., 1994). Customers, inespective of the sector, buy products and servicess to accrue benefits from them. These benefits are what lead to customer value (Gronoos, 2017). Organisations should thus understand what customers look for and what they evaluate and use these to determine customer requirements and design their service to meet these requirements. This is especially important for an organisation looking to launch a new product. For public sector organisations, this has not taken root as firmly as it has in private sector organisations (Rishel, Glover, & Niems, 20 18). This is likely because, for private sector organisations- their purpose is clear; profitability. Historically, 3 this purpose was not always clear for public sector organisations since many of them were formed to deliver for the 'well-being' of the society as a whole (Donnelly, 1999). In the current environment however, there is increased need for public sector organisations to become sustainable, increase productivity and contribute towards revenue generation for the national budget (Osbome, 1993). This is intensified by the fact that public sector initiatives tend to be capital intensive and are generally financed through debt. In addition, public sector organisations are often providers of unique services which private sector may shy away from perhaps due to their capital intensive nature thereby becoming monopolies. Despite being monopolies, substitutes may exist in the market for some services. As a result of this, organisations in the public sector are now facing situations where they have to compete with private sector organisations (Fountain, 2002). Generally, a negative correlation is assumed between monopolies and service quality and satisfaction (Noor & Nasimn, 2015) yet service quality is impm1ant in allowing an organization to differentiate itself from competitors thereby increase market share and profitability. Services are no longer delivered to passive recipients and customers now have greater purchasing options and transparency (Ghobadian et al., 1994). There is thus a strong case for organisations to discover customers' wants and needs and provide quality services that match customer expectations as closely as possible (Wisniewski & Donnelly, 1996). If public sector organisations are to improve their success rate in generating revenue, then increased focus on service quality and market perfmmance is necessary. Since customers receive services from both public and private organisations they sometimes compare the services offered by the two, despite the fact that these services may be different. As a result, service expectations for public sector organisations are on the rise made (Ghobadian et al. , 1994; Wangenheim, 2005). Market perfonnance is multidimensional in nature and that which constitutes marketing performance may vary between organisations (Gao, 2010). For purposes of this study, Gaal ' s (2008) market performance definition that relies on the psychographic factors increasing reputation, preferences, satisfaction, re-buying and to achieve buying intention was adopted and used to measure market perfmmance. Of these psychographic factors, the study focused on 4 achieving buying intention as measured through influence from word of mouth communication. According to Mangold, Miller and Brockway (1999), word of mouth communication has a significant effect on consumer purchasing behaviour. 1.1.3 Word of Mouth Communication Word of Mouth (WOM) is described as a process where interpersonal communications between parties has the ability to influence the receiver' s behaviour. It is therefore important for influencing purchase intentions as well as for promotion purposes. As a result, WO M influence is of pa11icular interest when marketing a product and is considered a significant way to obtain competitive advantage (Sweeney, Soutar, & Mazzarol, 2008). Literature categorises WOM into negative and positive WOM and it has been hypothesized that effects of negative WOM are stronger than that of positive WOM. Some studies highlight that negative WOM may prevent customers from choosing a product/service from a public sector organisation where comparisons with existing private sector products/services are made (Ghobadian et al. , 1994; Wangenheim, 2005 ; Wisniewski & Donnelly, 1996). Other studies however suggest that this is not the case and that both negative and positive WOM have equal influence on receivers ' behaviour (Sweeney et al. , 2008; Wangenheim, 2005). 1.1.4 Overview of Standard Gauge Railway Freight Services The focus of the study was the Standard Gauge Railway (SGR) freight services which are driven by a public sector organisation. SGR is a high capacity high speed railway for freight and passenger transpot1ation that connects Mombasa to Nairobi (Phase 1) and Nairobi to Naivasha (Phase 2) and Naivasha to Malaba (Phase 3) (Kenya Railways, 2018). According to The Budget Summary for the Fiscal Year 2017/18, Phase I of SGR, which is now complete, was constructed at a cost of KShs. 327 billion. (The National Treasury- Government of Kenya, 2016). This makes it the most expensive infrastructure project Kenya has embarked on since it gained independence in 1964. The SGR was funded mainly through debt with the People's Republic of China funding 85% and the Government of Kenya funding 15% and it is expected that revenues from the railway operations shall be used to repay the loan (National Assembly, 2014). To enable this, revenue 5 generation is a critical success factor in this project. SGR has two key product lines- Passenger services which transports passengers and freight services which transp011s cargo. Cargo services were launched by the president on 16 December, 2017 with operations beginning in January, 2018 (Kenya P011s Authority, 2018). 85% of intemational cargo comes through the sea with the main p011 in Kenya being Mombasa port (Kenya Ports Authority, 20 18). Transport to destination is mainly by rail or road. This means that whereas there is en01mous potential for an increase in market share for SGR, it is effectively competing with road transport (a substitute product). According to various newspaper rep011s, the govemment put in place various measures to drive uptake of SGR freight services including the reduction of container handling charges, the promise of faster service and directing that all un-nominated and govemmental agency cargo be transpot1ed to Nairobi via SGR. Stakeholders have raised various concems including speed and inefficiency of service delivery (Andae, 2019; Wachira, 2018; Wainainah, 2018). This study focused on the SGR freight services from a clearing agent perspective. A clearing agent is an entity that handles customs clearance on behalf of imp011ers (Manaadiar, 2019). In Kenya, only clearing agents can clear goods, importers thus appoint clearing agents to clear goods on their behalf. Clearing agents must be licensed by Kenya Revenue Authority in order to operate (Kenya Revenue Authority, 20 19). 1.2 Statement of the Problem Achieving service quality requires that organisations invest resources to increase both. (Sachdev & Verma, 2004). In order to invest limited resources efficiently, organisations need to establish the service quality dimension most likely to drive market perfonnance in their environment. Caceres & Paparoidamis (2004) sought to understand the relationship between service quality and marketing performance in business to business markets. Their study highlights the fact that whilst researchers have discussed the competitive advantages that could be gained from an improvement in service quality, very few have clearly demonstrated which of the service-quality dimensions might influence market performance in the information technology sector as manifested through 6 purchase decisions. It further identifies two service quality dimensions likely to influence satisfaction thus providing managers with strategic areas in which to enhance satisfaction levels. Grubor, Salai , & Lekovic (20 19) in their mticle service quality as a factor of marketing competitiveness highlight that in the customer relationship management approach, service quality is a basis for customer attraction and retention, as well as being a source of long-te1m and sustainable competitive advantage. This is augmented by the fact that marketing strategies based on quality lead to a recognizable image in the market which is difficult for competitors to appropriate or copy. Esmaeilpour, Mohamadi, & Rajabi (2016) expressed in their results of their research that the quality of services and its dimensions have a positive and significant impact on the brand equity and that customers want more value in exchange for payment. Liu & Wang (2017) attempt to understand the correlations between service quality and customer loyalty using repurchase intention, primary behaviour and secondary behaviour for the customer loyalty scale. They conclude that there is a positive relationship between these two constructs. Odeny (2016) in her study concludes that service quality has a significant influence and plays an impmtant role in the business performance of Barclays Bank of Kenya Limited. Nganga (2009) in a study examining the relationship between service quality, fi1m innovation and fitness enterprises perfmmance found that fitness managers should adopt managerial principles that make their enterprises more market oriented by developing systems of gathering market information and transfmming it into perfmmance outcomes aimed at enhancing customer orientation, service development, customer satisfaction, infmmation flow and market planning in order to enhance firm performance. Munene, 2016 in the study on the relationship between service quality and operational performance of public hospitals in Kenya determines operational performance using the constructs quality, flexibility and speed. Wambugu, 2018 in the study to determine the effect of service quality dimensions on customer satisfaction among government Huduma Centres in Kenya observes that customers in Huduma Centres generally recommend these services to other people with reliability and accessibility being significant determinants of satisfaction. While these studies highlight the growmg role of service quality as a factor of marketing performance and competitiveness in private sector organisations and others the relationship between service quality and operational performance in public sector organisations (hospitals) and 7 service quality and customer satisfaction (service centre), they have not holistically addressed the contribution of service quality to market perf01mance in the public sector more so the cargo transp011 industry leaving a contextual gap. This left a research gap that needed to be addressed. The purpose of this study was to determine the effect that service quality has on the market performance of SGR freight services. The choice of SGR freight services as a specific product to study was based on the fact that despite SGR freight services being a monopoly product mn by a public sector organisation and the various initiatives by the Government of Kenya to drive its use, it is cutTently not operating at full capacity (Andae, 2019; Wachira, 2018; Wainainah, 2018). SGR' s infrastmcture was funded through public debt (National Assembly, 2014) and there is therefore need for it to generate revenue to enable it contribute to the national budget, achieve sustainability and profitability. Increasing market share therefore becomes key in driving market performance. 1.3 Research Objectives 1.3.1 General Objective The main objective of the study was to establish the influence of service quality on market performance of SGR freight services from a clearing agent perspective. 1.3.2 Specific Objectives There specific objectives of the study were: 1. To establish the perception of the service quality of SGR freight services by clearing agents. 2. To detennine the influence ofWOM on achieving buying intention ofSGR freight services for clearing agents. 3. To establish the service quality dimensions that are most likely to influence market performance of SGR freight services as determined by clearing agent's future purchase intention. 8 1.4 Research Questions 4. What is the perception of service quality of SGR freight services by clearing agents? 5. What is the influence ofWOM on achieving buying intention of SGR freight services for clearing agents? 6. What are the service quality dimensions that are most likely to influence market perfonnance of SGR freight services as determined by clearing agent ' s future purchase intention? 1.5 Scope of the Study The study was limited to the influence of service quality on market performance as determined by the psychographic factor achieving buying intention. It focused on clearing agents as licensed by Kenya Revenue Authority that had cleared goods since SGR freight services which were launched in Kenya in January 2018. The decision to use clearing agents was based on the fact that they are mandated by law to clear cargo on behalf of impmters (Kenya Revenue Authority, 2018) and therefore have considerable influence on the choice on mode of transport. The study was a cross- sectional study conducted in April, 2019 in Mombasa (Mombasa Pmt) and Nairobi (Inland Container Depot- Nairobi) - the only two towns cuiTently connected to the Standard Gauge Railway through which SGR freight services are offered. 1.6 Significance of the Study The study findings are beneficial to Kenya Railways as it establishes the perception of service quality by clearing agents using SGR freight services thereby enabling them understand their customers' expectations thus offering guidance on how they can offer better service and inform their service strategies. The study fmther determines the service quality dimensions that positively impact market performance of SGR freight services. This is important as it provides policy makers and Kenya 9 Railways with an objective mechanism to detetmine the key drivers of service quality that they should invest in order to gain sustainable competitive advantage, increase market perfonnance and revenue of SGR freight services. This is especially critical to enable the product become sustainable given the heavy capital investment made on infrastmcture to mn the service. The study findings are also beneficial to service and marketing practitioners in the public sector who can use the study results to formulate service quality policies and standards aimed at increasing market performance. The study contributes to the present body of knowledge in service quality theory by detetmining the effect of service quality on market perfonnance by illustrating the influence of WOM on achieving buying intention thereby enabling scholars, academics and researchers in service marketing enhance their understanding in this area. 10 CHAPTER TWO: LITERATURE REVIEW 2.1 Introduction This chapter discusses the theoretical and empirical literature covering the effect of service quality on word of mouth influence. It presents the various theories supporting the variables, highlights the empirical studies carried out in the research area, presents the conceptual framework stating the relationship between variables and finally highlights the research gaps. 2.2 Theoretical Foundation Various theories offer an appealing framework for understanding service quality, word of mouth communication, service quality dimensions and achieving buying intention. This section highlights two of these theories; the Cognitive Dissonance Theory and the Theory of Planned Behaviour. 2.2.1 Cognitive Dissonance Theory The Cognitive Dissonance Theory (CDT) that was introduced by Leon Festinger in 1957. Elkhani and Bakri (20 12) summarise CDT as a theory that matches a person ' s expectations of something with its perfmmance in the real world. Dissonance between these two causes an unpleasant feeling. The theory proposes that an individual ' s actions result from their beliefs/ attitudes, and that dissonance could influence people' s decision-making processes. CDT has been used to explain consumer behaviour. Cognitive dissonance can occur at various stages of the consumption process. This has implications in that cognitive dissonance plays a role in the formation of service perceptions in various ways. Firstly, customers' perceptions of service quality changes as expectations change (Kim, 2011). Further, service characteristics such as va1iability mean that consumers rely on refeiTals to make a purchase in a bid to reduce perceived risks resulting in a situation where WOM has significant influence on purchase decisions in the service industry (Sweeney et al., 2008). 11 Kim (2011) highlights that individuals seek ways to reduce cognitive dissonance since it is an uncomfmiable state. In the context of word of mouth, people are motivated to reduce dissonance by spreading WOM messages: positive WOM for newly chosen altematives to suppmi the existing cognition and negative WOM for dropped altematives (Wagenheim, 2005). Recipients of negative WOM avoid cognitive dissonance by avoiding purchase unless they have had a positive interaction with the service provider in which case they ignore or downplay the importance of the message (Kim, 2011 ). For these reasons, Kim (2011) argues that cognitive dissonance plays a significant role in influencing consumers purchase intentions. The CDT has been extended into the Expectancy Disconfinnation Theory (EDT) which states that consumers have different expectations of quality of service based on their previous experiences, word of mouth and in other ways (Elkhani & Bakri, 2012). According to Spreng and Page Jr. (2003), disconfirmation occurs when there is a difference between the customer' s expectation of service and the outcome. Disconfinnation can either be positive (when outcome exceeds expectations) or negative (when outcomes fall short of expectations). Where the outcome matches the expectation, confirmation occurs (Oliver, 1980).It is this level of expectation that fmms the standard against which a product/ service is evaluated (Oliver, 1980). The service quality gap concept proposed by Parasuraman, Zeithaml and Beny (1985) is built on EDT and measures the gap between customers expected service and the outcome of what they actually receive. It is stated as: Q=P-E where: Q- Quality of the service P- Perception of delivered service (Outcome) E - Customer Expectations Festinger' s (1957) CDT and subsequent EDT and service quality gap concept provides the theoretical framework that this study used. He defines cognition as knowledge, opinion or belief about the environment or one' s behaviour and further proposes that dissonance is a motivating 12 factor and that it can be substituted with similar notions such as frustration. These arguments supp011 the premise on which this study is based that WOM influences purchase decisions. It used to better understand the relationship between WOM communication and buying intention. 2.2.2 Theory of Planned Behaviour The Theory of Planned Behaviour (TPB) predicts an individual's intention to engage in a behaviour at a specific time and place. It states that individual behaviour is driven by behaviour intentions where behaviour intentions are a function of three determinants: an individual's attitude toward behaviour, subjective nmms, and perceived behavioural control (Ajzen, 1991 ). Cheon, Crooks, Chen and Song (2012) define attitudinal beleifs as positive or negative feelings. They fm1her highlight that subjective norms are driven by social pressure and individuals integrate others opinions and perfmm similar behaviour to these other parties. For perceived behavioural control Giles, McClenahan, Caims and Mallet (2004) propose that customers judgements are influenced by factors outside their control. Figure 2.1: Theory of Planned Behaviour Perceived Behavioural Attitudinal Beliefs Subjective Norm Control Behavioural Intention Source: Adapted from A}z en, 1991 According to Conner and Armitage (1998), behavioural intention is a measure for behaviour and generally, the stronger the intention, the more likely the behaviour will be performed. It further states that when fmmulating the questionnaire- a clear definition of the behaviour of interest must be clearly defined in terms of its target, action, context, and time elements, the research population 13 must be specified and direct measures for attitudinal beliefs, normative beliefs and control beliefs fmmulated. TPB was used to formulate the research model. For purposes of this study, the behaviour of interest is achieving buying intention and was defined as 'clearing agents voluntarily nominating cargo to be transpotted using SGR freight services within the next one year' . The direct measures were; for attitudinal beliefs perceived service quality, for subjective notm social influence from positive WOM recommendation and for perceived behavioural control customers ' judgement about the extent to which their decision is influenced by service quality dimensions. 2.3 Empirical Review This section highlights existing literature on service quality, word of mouth communication, service quality dimensions as well as their relationship with market performance and with specific focus on buying intention. 2.3.1 Service Quality Service quality which is described as a measure of how well a service delivered matches customer expectations is a subject widely reviewed in literature since the mid 1980' s with Parasuraman, Zeithaml & BetTy (1984), Cronin & Taylor (1992), Gromoos (1988) and Oliver (1990) being key names in this area. The service industry has gained prominence in organisations today thereby driving higher levels of service quality is seen a competitive tool for organisations (Cronin & Taylor, 1992). Ghobadian, et al., (1994) state that according to the Profit Impact of Marketing Strategy (PIMS) database, ' companies with perceived high-quality goods and services typically had higher market share, higher return on investment and asset turnover than companies with perceived low quality' Pg. 43. This is driven by the fact that consumers prefer higher levels of quality for services/ products. Prentice (20 13) however notes that 'despite the fact that service quality is an important determinant of customer retention, an organisation ' s service resources are limited, and customers are not served equally; nor are all customers equally profitable to the firm. ' Pg. 51. 14 2.3.1.1 Measuring Service Quality and Service Quality Dimensions How service quality is measured and service delivered therefore becomes key. Genestre and Herbig (1996) argue that unless quality can be defined and quantified, it cannot be improved. This is however a complex process. Gromoos (1988) observes that service has various meanings ranging from personal service to service as a product. Fm1her, quality perspectives differ between the customer and the service provider. In addition to these arguments, Lehtinen and Lehtinen ( 1982) differentiate between the quality associated with the process of service delivery and the quality associated with the outcome of service delivery. Various arguments have been put forth with respect to measurmg servtce quality. The SERVQUAL model was developed by Parasuraman et al (1988) proposed that disconfirmation between expectations and perception be used and considers five dimensions of service quality namely reliability, assurance, tangibles, empathy and responsiveness. Wanyoike (2018) observes that these dimensions do not contribute equally to customer purchasing behaviour and that the attributes that customers value most vary from one industry to another. This position is consistent with Johnson, Tsiros and Lancioni (1995) assert that service is multifaceted and it is important that a company have the ability to distinguish and evaluate each ofthese areas independently. Babakus and Boller, 1992 suggest that service quality is either industry or context specific and therefore having a universal service quality constmct is oflittle utility value. Buttle (1996) highlight that the five dimensions are difficult to replicate across diverse service contexts. Further, SERVQUAL has a fixed criterion to judge customers' perception of service quality, and is criticised for lacking the ability to capture the probability that factors such as mood, past experience and customers' familiatity with the product or service may influence the outcome (Carman, 1990). Despite these sentiments, various researchers use SERVQUAL as an instmment to operationalize service quality and highlight that is a good predictor of overall service quality (Chaniotakis & Lymperopoulos, 2009; Choudhury, 2014). This could be because it 'provides a basic skeleton which can be adapted or supplemented to fit specific research needs of a particular organization.' (Parasuraman, Zeithaml, & BetTy, 1986) The SERVQUAL instmment is operationalized usmg 22 variables representing the five dimensions of service quality. Adil, Al Ghaswyneh and Albkour (2013) highlight that: 15 'The SERVQUAL instmment has two types of items, one to measure expectations about firms in general within an industry and the other to measure perceptions regarding the patticular company whose service is being assessed. The quality gap (Q) is calculated by subtracting the expectation (E) from the perception (P) value i.e. P-E = Q. Summation of all the Q values provides an overall quality rating which is an indicator of relative impmtance of the service quality dimensions that influence customers' overall quality perceptions.' Pg. 67 In order to rate both perfmmance and expectations, SERVQUAL studies use 44 statements in their research instmments (Polyakova & Mirza, 2015). Table 2.1: Dimensions of Service Quality Dimension Description Number of Variables Responsiveness The willingness to help customers and provide 4 prompt suppmt. Assurance The knowledge and courtesy of employees and their 4 ability to convey tmst and confidence. Tangibles The appearance of physical factors such as 4 equipment, facilities and personnel. Empathy Providing individual attention and care to customers. 5 Reliability The ability to perform the promised services 5 accurately and dependably. Source: Adapted fi'om Adil, AI Ghaswyneh and AlbkoUJ', 2013 Despite various critisms, the SERVQUAL model is one of the most dominant and popular methods through which service quality has been measured over the last 30 years. Numerous studies feature applications or adaptations of the SERVQUAL model. 16 Cronin and Taylor (1992) in their study 'Measuring Service Quality: A Re-examination and Extension ' investigate how service quality should be conceptualized and measured. They describe service quality as an attitude and asse11 that the SERVQUAL model fails to take this into account. They introduce the SERVPERF model which proposes that customer perceptions of the performance of a service is adequate to measure service quality. They conclude that service quality should be conceptualized and measured as an attitude and develop a performance-based scale to address this perceived sh01tcoming of SERVQUAL. It also attempts to remove the dist01tions caused by measuring expectations. The SERVPERV model consists of22 perception components excluding any considerations of expectations. SERVPERF has however been described as a sub- set ofSERVQUAL (Gronroos, 2001). According to Rodrigues, Barkur, Varambally and Motlagh (2011) as quoted by Polyakova & Mirza (2015), SERVPERF and SERVQUAL considerably differ in tenns of the outcomes of their two metrics and suggest that both should be applied and combined implications drawn. Polyakova & Mirza (20 15) however continue to state that according to Can·illat et al. (2007, the SERVQUAL scale is richer in its diagnostic value as it compares customer expectations of service versus perceived service across dimensions. Brady, Knight, Cronin Jr. , Hult, and Keillor (2005) introduce the Comprehensive Model which argues that service quality, sacrifice, satisfaction and value all play a role in influencing behavioral intentions. More recent studies highlight the need to introduce new ways of measuring service quality and present the idea of 'Service Encounters ' as a key driver of service quality (Stacey & Bick, 2014 and Whyte & Bytheway, 2017). It has been argued that constructs of service quality developed for one culture may not be applicable in another (Ladhari, 2008). Raajpoot (2004) introduces PAKSERV which is used for measuring service encounter quality in non-Western countries. This model includes Gronroos ' s ( 1984) technical and functional quality and Rust and Oliver's (1994) service performance and service environment elements of quality. It was developed for the Asian context (Pakistan) and Ladhari (2008) advocates that further research into culture and service quality is required as is the continued validation of PAKSERV in different cultural contexts. Saunders (2008) conducted a study using P AKSERV in South Africa and concluded that cultural dimensions are important in measuring service quality thus service quality scales should include cultural dimensions. 17 PAKSERV (Raajpoot, 2004) contains 24 components and six dimensions namely tangibility, reliability, assurance, sincerity, formality and personalization. It alters SERVQUAL by replacing the responsiveness and empathy dimensions with three alternative dimensions. This is done basis that using Hofstede' s cultural dimensions; power distance, individualism and uncertainty avoidance. Pakistani culture is considered to be one of high uncertainty. In a service setting, this translates to people seeking advice prior to a purchase to reduce the risk of dissatisfaction with a purchase - this is measured using the dimension sincerity. Fmther, power distance and individualism have been translated into the dimensions formality and personalization (Kashifa, Ramayahc, & Sarifuddin, 20 14). A comparison in Hofstede' s cultural dimensions; power distance, individualism and unce1tainty avoidance between Pakistan (for which PAKSERV was developed), Kenya (where this study was conducted) and America (where SERVQUAL was developed) yields the following results . Figure 2.2: Comparison of Hofstede's cultural dimensions for Pakistan, Kenya and America ' United States x 91 70 70 60 62 55 50 50 46 40 I 25 I 14 I I PovJer Individualism llasculinity u certainty Dis ance Avoidance Source: Adapted from Hofstede Insights (2019) Whereas for the cultural dimension individualism, the Pakistani and Kenyan scores are relatively close, the difference in scores for power distance and unce1tainty avoidance are relatively high with the difference being 25% and 20% respectively. 18 In their study in a public university library in Bangladesh, Ahmed and Shoeb, 2009 explore the users ' desired expectations for excellent service quality. They employ a modified version of the SERVQUAL questionnaire by adding an additional parameter- customers desired expectations. The study concludes that the original five dimensions identified by Parasuraman et al. are not applicable to library services. Gambo, 2016 in his study adopts a modified SERVQUAL model consisting five dimensions namely the check-in process, in-flight services, reliability, responsiveness and baggage handling services. The study concludes that airlines in Nigeria stand to lose customers if they fail to improve reliability and responsiveness to customer demands. In their study in public transpmt systems Beirao and Cabral (2006) highlight that service quality is perceived as an impmtant determinant of users' travel demand. They study concludes that in order to develop strategies to increase demand and use, knowledge of individual customer behaviour is impmtant. In addition, insights from non-users are cmcial in determining their reason for non-use and possibly uncovering initiatives aimed at changing behaviour (Ghobadian, Speller, & Jones, 1994). This study adopted the SERVQUAL gap model which is based on the assertion that service quality is the discrepancy between expectations and performance operationalized as the difference between the two constmcts represented as Service Quality= Performance- Expectation (Spreng & Page Jr. , 2003). 2.3.1.2 Improving Service Quality According to Mazur ( 1993 ), House of Quality (H OQ) is a tool for improving or evaluating service quality and observes that an absence of problems in service delivery does not necessarily translate to competitive advantage since customers expect that this should be the case. He highlights that in addition to eliminating poor service, organisations should maximise positive quality by discovering and delivering attributes that excite customers. To effectively achieve this therefore, organisations must understand how meeting customer requirements affects satisfaction. This view is consistent with Genestre and Herbig (1996) who state that: ' If a company wishes to prosper, it must first identify those elements that its client base believes to be important, create a product reflecting those elements and then train its providers to adopt the customer's definition of quality and not their own ' (p. 73) 19 Quality improvement techniques are however expensive and should therefore be prioritised. To achieve this, an organisation should develop a three dimensional service HOQ. This maps customer requirements against service characteristics and tracks the corresponding quality gain and cost (Zhang & Wang, 2012). Schneider, Chung and Yusko (1993) assert that since services are relatively intangible, they yield experiences rather than tangibles and for this reason emphasis on organisational systems that affect customer reactions to service offerings is key. They fmther highlight that service climate for service quality is key and is influenced by the contact customers have with employees during service delivery and the logistical or operations systems which have the ability to either facilitate or inhibit customer experiences. Sahai and Jain (2014) state that in the SERVQUAL model, the five dimensions of service quality all touch on the behavioural aspects of dealing with customers with the exception of tangibles. Sachdev and Ve1ma (2004) highlight that the fact that there are five quality attributes is essential to service marketing but is not sufficient. Thet state that knowledge on the most valued attribute is key. 2.3.2 Market Performance Critics of marketing commonly allude to problems with its accountability and credibility and must demonstrate the contribution of marketing to finn perfmmance (Gao, 201 0). Gaal (2008) highlights that market performance can be measured through the factors increasing reputation, preferences, satisfaction, re-buying and achieving buying intention. According to Mangold, Miller and Brockway (1999), word of mouth communication has a significant effect on consumer purchasing behaviour. 2.3.2.1 Word of Mouth Communication 76% of all purchase intentions are impacted by Word of Mouth (Jalilvand et al., 2017). WOM communication is carried out by individuals who are perceived as being independent from the company (Silvennan, 2011 ). It refers to the sharing of opinions from one consumer to another and is thought to be the outcome of a customer's experience with a product or service (Buttle F. A., 1998). Jalilvand et al. , 2017 argue that it is a procedure of choice for selling services in and environment where traditional marketing techniques are on a decline and that successful experiences trigger adoption behaviour. Two aspects ofWOM have been studied the most; volume 20 - the total number of interactions and valence - the nature of the interactions (Sivadas & Jindal, 2017). An important question therefore is how organisations can identify factors that influence WOM delivery. Research identifies key categories in word of mouth influence; positive and negative (Ghobadian, et al., 1994; Sweeney, Soutar, & Mazzarol, 2005; 2014) and highlights that both these categories of WOM have influence on consumers behaviour. Both positive and negative WOM are strategically important to a company (Anderson, 1998), however, various researchers asse1t that negative WOM is more influential that positive WOM (Ito et al., 1998) and cite various reasons for this. Kalmeman and Tversky ( 1984) highlight that the threat of potential loss is more influential than the hope of potential gain. Negative WOM may also prevent new customers from choosing a service provider (Wagenheim, 2005). This position contrasts with research from East, Hammond and Lomax, (2008) which suggests that more individuals purchase decisions are influenced more by positive WOM than they are by negative WOM. Ghobadian, et al., (1994) fmther highlight that whilst positive word of mouth can be a very powerful tool for attracting new customers, negative word of mouth can detract from the effectiveness of organizations' efforts to attract new customers. Sweeney, Soutar, & Mazzarol (20 14) however note that positive brand equity acts as a buffer to negative WOM. WOM is influenced by a range of factors. Sweeney et al. (2014) state that negative WOM is driven by emotion resulting from dissatisfaction whereas positive WOM is primarily driven by service quality. According to Cheng, Lam and Hsu (2006), negative WOM can be categorized based on customer intentions. Sundaram, Mitra, and Webster (1998) further highlight that motivations of negative WOM can be broadly categorized as altmism that aims at alerting others of risk, vengeance/ retaliation whose intent is to hmt the seller, anxiety reduction and advice seeking. These categories of intent tie in with the theory that dissatisfaction prompts individuals to engage in negative WOM as a means of reducing cognitive dissonance. Sweeney et al. (2014) further state that interpersonal factors such as the sender and receivers' expertise, the strength of the message and service product factors (prior experience with the service provider) impact WOM influence. 21 According to Buttle ( 1998), as cited in Lan, Liu, Fang and Lin (20 12), WOM influences awareness, expectations, perceptions, attitudes, behavioural intentions and behaviour. Parasuraman et al. (1985) and Choudhury (2014) both highlight a positive relationship between service quality and customers' willingness to recommend a company or product. Parasuraman et al. (1985) fmther highlight that Word of Mouth communications influence a customers expected service. Figure 2.3: Antecedents to Customers Expected Service Word of Mouth Communications Personal needs Past experience Expected Service Source: Parasuraman et al. (1 985) In their study (Jalilvand et al. , 2017) conclude that quality and value of restaurant products/ services influence customer WOM communication. It further reveals that food quality and physical environment and personal interaction between staff and customers has a positive effect on customers' perception of quality. Choudhury (2014) concludes that there is a strong relationship between service quality and WOM communication in the banking sector in India. WOM communication is subliminal. To counter this, influence of WOM communication can be operationalised by measuring behavioural intention. Zeithami et al (1996) developed a conceptual model that measures the effect of service quality on word of mouth communications (the customers ' intention/likelihood to recommend) and purchase intentions (the customers likelihood to do more business with the company). Chaniotakis and Lymperopoulos (2009) use this model in the context of the healthcare industry. 22 2.4 Conceptual Framework Based on the literature reviewed, the below conceptual framework was developed. The diagram illustrates the relationship between service quality (independent variable) and market performance (dependent variable). Service Quality is achieved if customer expectations are satisfied, or exceeded and was measured as Perception of Delivered Service (P) - Expectations (E). Market performance was determined by consumers' intention to buy measured by the rate at which clearing agents state that they would voluntarily nominate cargo to be transported using SGR freight services within one year. TPB was used to formulate this research model. The variables are based on direct measures as defined in the TBP. For attitudinal beliefs - perceived service quality, for subjective norm - influence of WOM communication on achieving buying intention of SGR freight services for clearing agents and for perceived behavioural control- customers' judgement about the extent to which their decision to use SGR freight services is influenced by the different service quality dimensions. Figure 2.4: Service Quality and Market Performance Independent Variable Intervening Variable Dependent Variables Service Quality Market Performance Dimensions Reliability Intention to buy Assurance Tangibles Empathy Responsiveness Source: Author (2019) 23 2.6 Summary of Literature and Research Gaps It is evident from the literature discussed that service quality should be approached from the customers ' perspective as it is the customer who is the judge of the quality of service. Despite being abstract in nature; it is considered a critical success factor for organisations that are striving to achieve competitiveness. The abstract nature of service quality is driven by the intangibility, inseparability of production and consumption, heterogeneity, and perishability of services (Kottler and Keller, 2016). SERVQUAL, which was introduced by Parasuraman et al. is a widely used service quality measurement model and its use is suppmted in various industries including hospitals (Chaniotakis & Lymperopoulos, 2009), restaurants, banks (Choudhury, 2014) and public land transpmt (Bakti & Sumaedi, 2015). Brysland and CuiTy (2001) highlight that literature also supports the use of SERVQUAL in the public sector. Despite SERVQUAL being popular, researchers posit that the nature of services should influence how service quality is measured. This has resulted in SERVQUAL being adapted to suit different industries. Market perfonnance is multidimensional in nature (Gao, 201 0). Gaal (2008) illustrates that market performance is affected by the factors increasing reputation, preferences, satisfaction, re-buying and to achieve buying intention. Service quality affects the purchase intentions of both existing and potential customers (Ghobadian, Speller, & Jones, 1994). WOM communication is also thought to be an outcome of service quality influence this relationship in either a positive or negative manner (Chaniotakis & Lymperopoulos, 2009). Literature also highlights various motives for consumer to engage in WOM including satisfaction or dissatisfaction with services received (Cronin & Taylor, 1992). WOM is best operationalized by measuring behavioural intentions. This study adopted the SERVQUAL model to measure service quality. This was operationalized as the difference between the two constmcts represented as Service Quality = Performance - Expectation (Spreng & Page Jr., 2003). Market performance was measured through the factor - achieving buying intention. 24 Service quality has a strategic role to play in the context of govemmental organisations offering a monopoly service in the transport sector (SGR freight services). This is due to the fact that despite the monopoly nature of the service offered, there still exist substitute services. It is therefore impmtant to determine the effect that service quality has on the behavioural intention of customers to drive revenue initiatives. Fmther, achieving service quality requires that organisations allocate resources into activities that will lead to the best value for the customers and the organisation (Sachdev & Verma, 2004). Determining what these activities are requires that organisations establish the service quality dimension most likely to drive market performance in their environment. Diverse studies examining the relationship between service quality, WOM and purchase intentions exist for various industries. These studies have however not holistically addressed the contribution of service quality to market perfonnance in the public sector more so the cargo transport industry leaving a contextual gap. This study addresses this gap. 25 CHAPTER THREE: RESEARCH METHODOLOGY 3.1 Introduction This study sought to determine the relationship between service quality and market performance of SGR freight services. This chapter outlines the research methodology that was followed for the study. It begins by describing the research design, then defining the respondents to the study, sampling techniques, data collection methods and data analysis techniques. It also seeks to illustrate how the study addressed research quality and ethical consideration. 3.2 Research Design According to Saunders et al. (2016), research design is the general plan of how the study shall answer the research questions. It seeks to give a detailed and cohesive account of how the researcher intends to go about identifying the sample, collecting, analysing and interpreting data in an attempt to answer the research question (s). An appropriate choice of the research design lends credibility and external validity to a study. In assessing the effect of service quality -on market perfmmance of SGR freight services, the descriptive research method which aims to produce an accurate representation of situations and correlational methods which aims to detetmine the extent to which various variables are related to each other were used to answer the research objectives. The research strategy employed was the descriptive design using a survey. The research was cross-sectional in nature and data was collected using questionnaires and analysed using quantitative techniques. In collecting and analysing data for question one- ' What is the perception of service quality of SGR freight services by clearing agents?' a descriptive research approach was used to help gather any insights. This is because this is the method best suited to give a better understanding of the perception of service quality ofSGR freight services by clearing agents. For question two- ' What is the influence of WOM communication on achieving buying intention of SGR freight services for clearing agents? ' and question three 'What are the service quality dimensions that are most 26 likely to influence market perfmmance of SGR freight services as determined by clearing agent ' s future purchase intention?' the correlational method was used to help establish the nature of the relationship between WOM communication and achieving buying intention as well as the service quality dimensions likely to influence the use of SGR freight services by clearing agents hence market performance. 3.3 Population and Sampling Frame The target population for this study was clearing agents. SGR cargo services were launched by the president on 16 December, 2017 with operations beginning in January, 2018 (Kenya Potts Authority, 2018). Kenya Revenue Authority is mandated to license clearing agents; 909 clearing agents were licensed in 2018 (Kenya Revenue Authority, 20 18). Due to financial and time constraints, the study could not collect data from the entire population. Saunders et al. (20 16) however highlights that sampling can provide data to accurately represent the population. 3.4 Sample and Sampling Technique To deliver accurate findings within a 5% margin of enor and 95% confidence level a sample size of270 was adopted. This was obtained using the below formula adopted from Bmtlett, Kotrlik and Higgins (200 1) . Z2 ·p(l-p) ez z2 . p(l- p)) 1 + ( e2N Where: Z =Confidence Level (@ 95% z- score is 1.96) p = Standard of Deviation (0.5) e =Margin of Error (5%- 0.05) N = Population size (909) 27 ( 1.962 X 0.5 (1-0.5)) -;- 0.052 I + {[ 1.962 X 0.5 (1-0.5))-;- [0.052 x 909)} = (3 .84I6 X 0.25] -;- 0.0025 I + {[3 .84I6 X 0.25) -;- [0.0025 X 909)} = 384.16 I.4226 =270 Non-probability sampling was used. The decision to use non-probability sampling was based on the fact whereas a customer may be randomly selected as a respondent, there is no guarantee that they would be reached or willing to respond. Convenience sampling was thus employed until the required sample size was obtained. 3.5 Research Instruments and Data Collection Techniques The study used the mono method quantitative approach which employs the use of questionnaires as the sole data collection tool. Daniel and Bemyuy (20IO) in their study 'Using the SERVQUAL Model to assess Service Quality and Customer Satisfaction.' bring the statements that measure expectations first to avoid potential bias in responses due to possible feelings triggered from experiences. This study therefore measured expectations before performance in an attempt to increase respondent objectivity. Choudhury (20I4) drop II items from the SERVQUAL list because they are either repetitive, meaningless or difficult for respondents to comprehend. He further operationalises WOM communication by measuring willingness to recommend and customers willingness to say positive things about the service/ product. The questionnaire for this study was operationalised with a five-point Likert scale and administered by three research assistants; two in Mombasa and one in Nairobi. The research assistants were briefed to get a basic understanding of the topic being studied and trained on how 28 to collect data using the prescribed questionnaire. The questionnaire was divided into four key sections with the first section comprising demographic data. The second section sought to determine service quality and adopted SERVQUAL's 22 item scale and compress them into 11 items to reduce the length of the tool by removing repetitive items and merging related items while categorizing them into the five dimensions of service quality. This section was then divided into two pat1s - one to measure expectation and the other perception. The expectation section required the respondent to indicate the extent to which the ideal service possesses the characteristic in each statement. The perception section required the respondent to indicate the extent to which SGR freight services possessed the characteristic in each statement. The third explored respondent's behavioural intentions and willingness to refer and use SGR freight services. The fourth section determined the SQ dimensions likely to influence SGR freight services. Table 3.1: Operationalisation of the Service Quality Dimensions - Adapted to SGR freight services Variable: Service Quality Sub-variable Indicator (As per SERVQUAL Adapted SERVQUAL scale scale) Responsiveness 1. Inf01m customers when service 1. Inform customers when (RES) will occur service will occur 2. Receive prompt service from 2. Receive prompt service from employees employees who are willing to 3. Employees willing to help help and respond to requests. 4. Employees respond to requests Assurance 5. Employees are tmstworthy 3. Served by employees that are 6. Customers feel safe in dealings tmstworthy and polite. (ASS) 7. Employees are polite 4. Employees have support to 8. Employees have support to do do their job well. their job well 29 Tangibles 9. Up-to-date equipment 5. There is up-to-date 10. Visually appealing facilities equipment (TAN) 11. Well-dressed employees 6. There are visually appealing 12. Facilities consistent with the facilities and well-dressed industry employees Empathy 13. Fitms provide individualized 7. I receive individualised attention attention (EMP) 14. Employees provide 8. I am served by employees individualized attention that understand my needs and 15. Employees understand have my best interests in customer needs mind 16. Employees have the best 9. They operate at convenient interests of the customer in hours mind 17. Operate at convenient hours Reliability 18. Respond within timeframe 10. They are dependable. 19. Reassuring when problems Respond within and deliver (REL) anse service within times 20. Dependable promised. 21. Service delivered at times 11 . They are reassuring when promised problems arise. 22. Accurate records 3.6 Data Processing and Analysis The data collected was recorded, checked for completeness and tested for normalcy. The responses to SERVQUAL's items were aggregated and summarized into the five dimensions of service quality. Measures of central tendency such as frequency and percentage distributions were used to present demographic data. SERVQUAL scores were then generated for each customer by subtracting the expectation score from the perception score for each item and aggregated. 30 Factor analysis of the SERVQUAL scores was then conducted on all the customers' responses and a compressed description of the 11 SERVQUAL items used in the study presented. Descriptive statistics such as mean and standard deviation was used to perform data analysis and highlight the perception of service quality by and behavioural intentions of clearing agents. The Spearman ' s rank correlation coefficient was applied to draw conclusions on the influence ofWOM communication on achieving buying intention for clearing agents. Binary logistic regression was used to predict the probability that each service quality dimension influences use of SGR freight services by clearing agents. Tables, Charts and Graphs were used to present all the data. 3. 7 Research Quality Saunders et. al. (20 16) state that ' reliability and validity are central to judgments about the quality ofresearch ' p. 9. 3.7.1 Reliability Reliability refers to the ability of a research design to be replicated and the same findings obtained. Saunders et. a!. (20 16). This refers to the consistency and repeatability of the results yielded by the research instrument. To address this the researcher documented the steps and tools used in canying out the study. Reliability of the various Like11 scales was assessed through the Cronbach ' s alpha (a) score. The study achieved an average reliability score of0.954. This was above the lower limit of 0.70 targeted by the study as recommended by Nunnaly (1978). A summary of the results is presented in the table below: Table 3.2: Reliability test results Scale Cronbach's alpha (a.) score Expectations 0.948 Outcome/ Perceptions 0.962 Behavioural Intentions 0.931 Influencing Dimensions 0.976 Source: Study data (2019) 31 3.7.2 Validity According to Saunders et. al. (20 16) external validity is defined as the ' extent to which result results are generalizable to all relevant contexts. ' p. 716. Extemal validity is achieved by providing a full description of the research questions, design, context, findings and interpretations, thus providing the reader with the opportunity to judge the transferability of the study to another setting in which the reader is interested in researching. To address this the researcher documented research questions, design, context, findings and interpretations used in conducting the study. Intemal validity is established when the research achieves the intended outcome. Orodho, (2009) states that validity of a research instrument is the degree to which results obtained from the analysis of the data represents the phenomenon under investigation. To achieve this the researcher carried out a pilot test of the research tool using four respondents to address errors in design of the instrument such as ambiguity. Although the initially proposed questions were well understood, it was proposed that the length of the questionnaire be reduced. The SERVQUAL instrument (operationalized using 44 questions) was found to be too long for purposes of this study. To avoid low response rates, an abridged version ofthe SERVQUAL instrument was administered. In order to ensure content validity, validity of the data was tested by comparing the abridged instrument against the SERVQUAL instrument to ensure it was relevant and representative. (Laerd Dissertation, 20 19) 3.8 Ethical considerations To address ethical considerations, the researcher maintained integtity and objectivity during the research. The researcher disclosed the purpose of the study to the respondents upfront and obtained their consent to ensure that respondent's participation was voluntary and that they were not coerced into answering questions they were not comfortable with. Respondents were also informed of their right to confidentiality and anonymity. No payments were made for patticipating in the research. Data collected was handled with due care. To maintain confidentiality and anonymity, data collected was grouped and respondents ' names and specific organizational affiliation were not collected. 32 CHAPTER FOUR: DATA ANALYSIS AND PRESENTATION 4.1 Introduction This chapter analyses and presents the results of the data collected to address the objective of the study which was to establish the influence of service quality on market performance of SGR freight services. The service quality variables were as described by the service quality dimensions namely reliability, assurance, tangibility, empathy and responsiveness and the market performance variable was achieving buying intention as determined by WOM. The study used a questionnaire to gather the information to be used in addressing the research question and the data was collected in April, 2019. 4.2 Response Rate According to Bartlett, Kotrlik and Higgins (2001), detetmining sample size and dealing with nonresponse bias is essential when dealing with a quantitative survey design. The study targeted a sample size of270 clearing agents in Kenya and achieved a total tally of273 completed responses representing a 101.1% response rate. The 273 responses were checked for completeness in the four sections of the questionnaire. This information is summarised in the table below: Table 4.1: Response Rate and Completeness Target sample size Responses Received Response Rate 270 273 101.1% Section Completeness % n Expectations 81.7% 223 Outcome/ Perceptions 78.4% 214 Behavioural Intentions 91.6% 250 Influencing Dimensions 75.8% 207 33 The Kaiser Meyer Olkin measure was used to test for sampling adequacy. Cerny and Kaiser (1977) indicate that a value above 0.8 indicates that the sample is adequate. The data set returned a value of 0.884 and was considered valid for analysis. The Bartlett's test of Sphericity returned a value of .000 which is less than 0.05 level of significance, factor analysis was therefore considered as an appropriate technique for further analysis of the data. Table 4.2: Kaiser Meyer Olkin (KMO) and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy .884 Bartlett' s Test of Sphericity Approx. Chi-Square 2028.077 df 55 Sig. .000 Source: Study data (2019) 4.3 Descriptive Statistics This section highlights the general profile of the 273 respondents that were involved in the study. 4.3.1 Gender Proportions From the total respondents, 71% were male, 24% female while 5% declined to indicate their gender. Figure 4.1: Respondent distribution by gender (Percentage) • Female • Male No Response 34 4.3.2 Proportion by ownership The data highlights that majority of the respondents were employees. From the total respondents, 89% were employees, 7% owners while 4% declined to indicate their status in the company. Figure 4.2: Respondent distribution by ownership (Percentage) • Owner • Employee No Response 4.3.3 Length of operation A review of the data based on the length of operation of the company's highlights that there was representation from all categories surveyed. The highest category was respondents from companies that have been in operation for above 20 years at 33%, closely followed by companies that have been in operation for 16-2.0 years at 31%. There was similar distribution of responses from companies that have been in operation for between 1-5 years and 6-1 0 years at 7% and 8% respectively. All in all, it was observed that 82% of the responses were received from companies that had been in operation for over 10 years. Figure 4.3 : Respondent distribution by length company has been in operation (Percentage) 40 31 33 30 18 20 7 8 10 0 0 II II I -2 Less than 1 1-5 6-10 11-15 16-20 Above 20 No Response 35 Served by employees that are trustworthy and 2.14 -0.62 polite Employees have support to do their job well 2.03 -0.69 Tangibles 2.310 - 0.480 There is up-to-date equipment 2.35 -0.50 There are visually appealing facilities and well- 2.27 -0.46 dressed employees Empathy 2.213 -0.583 I receive individualised attention 2.18 -0.57 I am served by employees that understand my 2.09 -0.74 needs and have my best interests in mind They operate at convenient hours 2.37 -0.44 Reliability 2.315 -0.69 They are dependable. Respond within and deliver 2.24 -0.66 service within times promised They are reassuring when problems arise. 2.39 -0.72 Average 2.204 -0.62 Source: Study data (2019) The service quality scores are all negative indicating that in general, customers' expectations exceed outcome highlighting that the services do not meet customers' expectations in all dimensions. The dimension with the highest dissonance is responsiveness followed by reliability with assurance coming in third. The data also illustrated that customers have highest expectations on employees have support to do their job well followed by they are informed when a service will occur and third that they are served by employees who understand their needs. When generalized, the dimension with the highest expectation was assurance, closely followed by responsiveness. Factor analysis was then conducted with the SERVQUAL scores for the entire set of customers. The aim of this was to explain any correlations among the outcomes obtained as well as identify any latent factors that may be influencing the variation (Choudhury, 2014). Subsequently, the 37 communality index, which is a representation of how well an item correlates with other items, was assessed. Cerny and Kaiser (1977) indicate that indices of 0.5-1 are desirable as they indicate that variations can be explained by the factor model. Communalities for this study are highlighted in Table 4.4. All the items were greater than 0.5 and were therefore included in the analysis. Table 4.4: Communality Index Initial Extraction Infonn customers when service will occur 1.000 .744 Receive prompt service from employees who are willing 1.000 .794 to help and respond to requests Served by employees that are tmstworthy and polite 1.000 .754 Employees have support to do their job well 1.000 .658 There is up-to-date equipment 1.000 .607 There are visually appealing facilities and well-dressed 1.000 .544 employees I receive individualised attention 1.000 .586 I am served by employees that understand my needs and 1.000 .682 have my best interests in mind - They operate at convenient hours 1.000 .728 They are dependable. Respond within and deliver service 1.000 .779 within times promised They are reassuring when problems arise. 1.000 .745 Source: Study data (2019) Guttman (1954) introduces the notion that only factors with eigenvalue greater than 1 should be retained. This mle is still applied to date. The data extracted two factors with an eigenvalue greater than 1. These two factors cumulatively account for 69.277 of the variance. This is represented in Table 4.6 and Figure 4.5 below. 38 Table 4.5: Eigenvalues Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings %of Cumulative %of Cumulative Component Total Variance % Total Variance % 1 6.313 57.387 57.387 6.313 57.387 57.387 2 1.308 11.891 69.277 1.308 11.891 69.277 3 .821 7.463 76.740 4 .567 5.158 81.898 5 .444 4.039 85.937 6 .402 3.651 89.588 7 .372 3.380 92.968 8 .281 2.559 95.527 9 .190 1.728 97.255 10 .173 1.570 98.825 11 .129 1.175 100.000 Extraction Method: Principal Component Analysis. Source: Study data (2019) Figure 4.5: Scree Plot Scree Plot c Of ·~---------------------------------------------------------- 2 4 7 9 Component Number Source: Study data (2019) 39 Tabachnick and Fiddell (2007) highlight that if factor con·elations are .32 and above, there is more than 10% variance and an oblique rotation method like direct oblimin should be used. The data set yielded factor correlations of .351 and Oblimin with Kaiser Normalisation was then applied to the data. The Rotated Factor Matrix represents the rotated factor loadings, which are the correlations between the variables and the factors. The component matrix in table 4.6 shows factor loadings based on the rotated component matrix. Table 4.6: Rotated Component Matrix Component 1 2 EMP8 .816 -.129 ASS4 .788 .191 TAN 5 .779 RES2 .760 .465 REL10 .760 -.449 EMP7 .760 EMP9 .746 -.414 REL 11 .741 -.443 ASS 3 .740 .454 TAN6 .736 RES 1 .702 .501 Extraction Method: Principal Component Analysis 2 components extracted Source: Study data (2019) The questions under each dimension were coded with RES representing Responsiveness, ASS representing Assurance, TAN representing Tangibles, EMP representing Empathy and REL representing reliability. The numbers then represented the question under each category. It is observed that all the variables have correlations above the .70 level with component 1. From the factor analysis, the variables aligned into the two extracted factors. The variables were included into each core factor then represented and named as per the data in table 4.7 below. 40 Table 4.7: Name of the two core factors Factor Variables Included Name of the Factor 1 RELlO They are dependable, respond and deliver service Accessibility and within times promised Effectiveness REL II They are reassuring when problems arise EMP9 They operate at convenient hours EMP8 I should be served by employees that understand my needs and have my best interests in mind EMP7 I should receive individualised attention TAN6 The facilities are visually appealing and the employees well-dressed TANS There is up-to-date equipment 2 RES 1 I should be informed when a service will occur Service Encounters RES2 I should receive prompt service from employees who are willing to help and respond to requests ASS 3 I should be served by employees that are trustworthy and polite ASS 4 Employees should have support to do their job well Source: Study data (2019) 4.6 Behavioural intentions The study sought to determine the influence ofWOM on achieving buying intention ofSGR freight services for clearing agents. A five-point Likert scale was used comprising the options strongly agree, agree, neutral, disagree and strongly disagree. The findings are presented in table 4.8 below. Table 4.8: Behavioural intentions for SGR Freight Services Frequency and Percentages Strongly Strongly Standard Count Agree Neutral Disagree Mean agree disagree Deviation N 1 2 3 4 5 41 10M 250 ommunication Tillingness to recommend N 55 39 68 69 19 2.82 1.268 GR freight services % 22 16 27 28 8 ikelihood of giving N 58 33 72 68 20 2.82 1.280 )Sitive WOM about SGR eight services % 23 13 29 27 8 ecommendation 250 tfluence kelihood of using SGR N 74 18 54 84 20 2.82 1.376 eight services upon ceipt of positive % 30 7 22 34 8 commendation uture Purchase 250 ehaviour Llture intention to use N 63 22 73 73 19 2.85 1.295 3R freight services % 25 9 29 29 8 Source: Study data (2019) 4.6.1 WOM Communication From the descriptive statistics generated whose findings are presented in Table 4.8 above, willingness to recommend stood at an average of 2.82 which is below the median point of 3 and had a mode of 4 (disagree). 38% of the respondents indicated their willingness to recommend SGR freight services with 22% strongly agreeing to the stateme11t and 16% indicating they agreed to the statement. Further, responses for likelihood of giving positive WOM recommendations stood at an average of 2.82 which is below the median point of 3 and had a mode of 3 (neutral). 36% of the respondents indicated the likelihood of giving positive WOM recommendations about SGR freight services with 23% strongly agreeing to the statement and 13% indicating they agreed to the statement. The box plot in Figure 4.6 below illustrates that there is an almost even distribution between the clearing agents willing to recommend and speak positively about SGR freight services and those who are not willing to do so. It can be inferred that there is a relatively low indication of intention to recommend SGR freight services. 42 Figure 4.6: WOM communication for SGR Freight Services Key 5 Strongly disagree 4 Disagree 3 Neutral 2 Agree 1 Strongly agree jl arnv.111mg lo rccomrnc•J:l SGR IIE19 : S·"Mccs lo lncnd anctor lmml;] Key 5 Strongly disagree 4 Disagree 3 Neutral 2 Agree 1 Strongly agree Source: Study data (2019) 43 4.6.2 Recommendation Influence For the statement determining the likelihood of whether clearing agents would be influenced to use SGR freight services upon receiving positive recommendations stood at an average of 2.82 which is below the median point of3 and had a mode of 4 (disagree). 37% of respondents indicated they were likely to be influenced by positive WOM recommendations with 30% strongly agreeing and 7% agreeing to the statement. The box plot in Figure 4. 7 below illustrates that more clearing agents indicate that they are unlikely to be influenced to use SGR freight services upon receiving positive recommendation when compared to those that who would not. The upper whisker indicates a variation in views in the segment of customers that is unlikely to be influenced. These findings can be presumed to be an indication that while positive WOM recommendations may influence uptake of SGR freight services, it is not a sufficient driver of uptake of the services. Figure 4.7: Recommendation Influence for SGR Freight Services Key 5 Strongly disagree 4 Disagree 3 Neutral 2 Agree 1 Strongly agree [I am hhe~1 to use SGR fr erglrt sc l\1ces rllrewrve a posrbve recornmondabon] Source: Study data (2019) 4.6.3 Future Purchase Behaviour Responses in this section stood at an average of 2.85 which is below the median of 3. The mode for this response was a tie between 3 (neutral) and 4 (disagree). 34% of respondents indicated the intention to use SGR freight services in the next year with 25% strongly agreeing and 9% agreeing to the statement. The box plot in Figure 4.8 below illustrates that there were more clearing agents 44 that indicated that they did not intend to use SGR freight services in the next year than those that did. In order to drive market performance ofSGR freight services, more effo11 needs to be put into driving purchase intention amongst clearing agents. Figure 4.8: Future Purchase Intent for SGR Freight Services Key 5 Strongly disagree 4 Disagree 3 Neutral 2 Agree I Strongly agree Source: Study data (2019) Responses assessing repeat purchase intent from clearing agents currently using the services yielded a mean of 2.78 which is below the median of 3 and had a mode of 4 (disagree). On the converse, responses assessing future intention to use SGR freight services from clearing agents not using the services yielded a mean of 3.02 which is slightly above the median of 3 and had a mode of 3 (neutral). Intention to use SGR freight services in the future was thus higher among clearing agents not using the service. This could be an indication that there is room for improvement in the service to enable it achieve higher levels of repurchase intention amongst existing customers. Table 4.9: Future purchase intent for clearing agents using and not using SGR freight services Frequency and Percentages Count Strongly Strongly Standard Agree Neutral Disagree Mean N agree disagree Deviation 45 1 2 3 4 5 uture Purchase Behaviour (Future intent to use SGR freight services) urrently using SGR n 58 14 55 60 15 2.78 1.29 eight services % 29 7 27 30 7 ot using SGR freight n 5 8 18 13 4 3.02 1.28 :fVICeS % 10 17 38 27 8 4.6.4 Relationship between WOM Communication and future purchase intent of SGR Freight Services This was measured using the Spearman's rank test to assess the relationship between the variables. The results are presented in table 4.10 below. Table 4.10: Spearman's Rank Correlation Test (WOM communication and future purchase intent) WOM Future Purchase Communication Intent Spearman ' s rho WOM Correlation 1.000 .593** Communication Coefficient Sig. (2-tailed) - .000 N 256 250 Future Purchase Conelation .593** 1.000 Intent Coefficient Sig. (2-tailed) .000 - N 250 250 ** Con·elation is significant at the 0.01 level (2-tailed) Source: Study data (2019) The test highlighted that there is a positive correlation between WOM communication and future purchase intention for SGR freight services among clearing agents indicating that there is social influence from positive WOM recommendation on market performance of SGR freight services. Evans (1996) verbally describes correlation strength as .00- .19 "very weak", .20-.39 "weak", .40- 46 .59 "moderate", .60-.79 "strong" and .80-1.0 "very strong". Using this scale, the level of conelation between the two variables can be desc1ibed as moderate at 0.593. 4.7 Influence of Service Quality Dimensions on Market Performance of SGR freight services as determined by intention to use/buy The study sought to establish the influence different service quality dimensions have on market performance of SGR freight services as dete1mined by intention to the services by clearing agents. A five-point Likert scale was used comprising the options strongly agree, agree, neutral, disagree and strongly disagree. The findings are presented in table 4.11 below. Table 4.11: Service Quality Dimension most likely to influence use of SGR freight services Service Quality Standard Skewness Mean Median Dimension Deviation (Pearson) Responsiveness 2.73 3 1.29 -0.63 Assurance 2.69 3 1.27 -0.73 Tangibles 2.63 3 1.31 -0.85 Empathy 2.55 3 1.31 -1.03 Reliability 2.68 3 1.28 -0.75 Source: Study data (2019) It was observed that the data was negatively skewed implying that in general, clearing agents regarded all dimensions as important and likely to influence their use of SGR freight services. This is underscored by the similarity in median ratings for the five dimensions and the closeness in value of the mean and median. A graphical representation of the responses received from clearing agents as illustrated in figure 4.9 has a comparable pattem for all dimensions further highlighting the similmity in importance in the five dimensions. Despite this however and using the mean, it emerged that the dimensions in order of importance were responsiveness (willingness to help customers and provide prompt support), assurance (knowledge and courtesy of employees and their ability to convey tmst and confidence), reliability 47 (ability to perform the promised services accurately and dependably), tangibles (appearance of physical factors such as equipment, facilities and personnel) and lastly empathy (providing individual attention and care to customers). Figure 4.9: Most influential/ important service quality dimensions Responsiveness Assu rance 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 0 I 0 I Strongly Ag ree Neutral Disagree St•rongl y Stron gly Agree Neutral Disagree Str•ong ly agree disagree agree di sagree Tangibles Empathy 100 80 80 60 60 40 40 20 0 I I • 20 0 I I I Strongly Agree Neutral Di sagree Strong ly • Strongly Agree Neutral Di sagree Strongly agree disagree agree di sagree Reliability 80 70 60 50 40 30 20 10 0 I Strongly Agree Neutral Di sagree Str•ong ly agree disagree Source: Study data (2019) 48 4.7.1 Service Quality Dimensions likely to influence Market Performance of SGR freight services as determined by intention to use/buy Of the 253 cases analysed, 79.8% indicated that they cun-ently used SGR freight services. Binary logistic regression was used to predict the probability that each service quality dimension influences market performance of SGR freight services as determined by intention to use the services by clearing agents. The percentage accuracy in classification was 80.7%. The Omnibus Tests of Model Coefficients canied out on the data set highlighted that there is some predictive capacity in the regression equation with a chi square value of 11.857 and significance of .037. The model explained 8% (Nagelkerke R2) of the variance in use of SGR freight services. The results are highlighted in table 4.12 below. Table 4.12: Binary logistic regression (Service quality dimensions and Market Performance of SGR freight services) Variables in the Equation B S.E. Wald df Sig. Exp(B) Step 1a Responsiveness (RES) .174 .272 .411 .521 1.190 Assurance (ASS) -.293 .339 .745 .388 .746 Tangibles (TAN) .754 .328 5.279 1 .022 2.126 Empathy (EMP) -.304 .295 1.061 1 .303 .738 Reliability (REL) -.581 .251 5.347 .021 .559 Constant 2.115 .479 19.499 1 .000 8.289 Source: Study data (2019) a. Variable(s) entered on step 1: Responsiveness (RES), Assurance (ASS), Tangibles (TAN), Empathy (EMP), Reliability (REL). Given that there is some predictive capacity vested in the model, the overall observation is that improvement in service quality across all dimensions would result in an increase in market performance of SGR freight services as determined by intention to buy. The relationships in order of influence as derived from the model are; Tangibles 2.126, Responsiveness 1.190, Assurance 0.746, Empathy 0.738 and lastly Reliability 0.559. Tangibles and Reliability are significant at the confidence level (< .05) and the relationship could be confirmed at a 95% significance level. 49 Responsiveness, Assurance and Empathy are not significant at the confidence level (> .05) and the relationship could not be confirmed at a 95% significance level. 50 CHAPTER FIVE: DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS 5.1 Introduction The study sought to determine the influence of service quality on market performance of SGR freight services from a clearing agent perspective. The objective of the study was to i. establish the perception of the service quality of SGR freight services by clearing agents, ii. determine the influence of WOM on achieving buying intention of SGR freight services for clearing agents and iii. establish the service quality dimensions that are most likely to influence the use of SGR freight services by clearing agents. This chapter presents a discussion of the study findings, draws conclusions from the findings and makes recommendations. 5.2 Discussion This section summarizes the findings as per the specific objectives of the study by comparing the literature review and quantitative results. 5.2.1 Overall Perception of Service Quality of SGR freight services by clearing agents The first objective aimed at establishing the overall perception of service quality of SGR freight services by clearing agents. A modified SERVQUAL scale was used in the study and the reliability coefficient (Cronbach ' s alpha) of the modified scale determined to be 0.948. Service quality was measured by determining disconfirmation between customers' perception of outcome and their expectations. The study findings revealed that discontinuation was negative for all dimensions, indicating that SGR freight services was failing to meet customer expectations. The dimension with the highest dissonance was dete1mined to be responsiveness. Responsiveness is primarily concemed with how service firms respond to customers via their personnel. This was followed by reliability, assurance then empathy. The dimension with the lowest dissonance was determined to be tangibility. The data also illustrated that customers have highest expectations in the parameter employees have suppmt to do their job well followed by they are informed when a service will occur and third that they are served by employees who understand their needs. The implication of this finding is that employees are key drivers of service quality for SGR freight services implying 51 that in order to enhance service delivery and improve service quality outcomes focus on employees and customer employee encounters is necessary. Factor analysis for the SERVQUAL scores was conducted and a two-factor solution obtained. The items were reconfigured into two dimensions aligning with the factors obtained. The first factor was defined as accessibility and effectiveness. Accessibility was determined to include working hours and routes/ distance to access the service. This is consistent with Wambugu, 2018 who in her study on Huduma Centres in Kenya determines accessibility to be a significant driver of servive quality. It is essential that matters relating to distance to access service and availability to serve in order to accommodate the needs of customers be addressed. Effectiveness was determined to be relative service performance as driven by ability to keep service promise and resolve issues; underpinning the need for focus on service and handling of customer problems and complaints. The second factor was defined as service encounters. Service encounters was determined to include provision of information on status of service and interactions with employees. Effective decision making and empowerment of customer facing staff is thus key to manage this dimension. This is consistent with Stacey and Bick (2014) and Whyte and Bytheway (2017) who present the idea of service encounters as a driver of service quality. 5.2.2 Influence of WOM on achieving buying intention of SGR freight services The second objective of the study sought to determine the influence ofWOM on achieving buying intention of SGR freight services for clearing agents. This was achieved by determining three parameters considered critical in answering the research question namely; WOM communication, recommendation influence and future purchase behaviour. In WOM communication, responses for willingness to recommend and likelihood of giving positive WOM about SGR freight services indicated that there is a low level of intention to recommend SGR freight services amongst clearing agents. This can be linked with the finding that SGR freight services was failing to meet customer expectations. For recommendation influence, more clearing agents indicated that they are unlikely to be influenced to use SGR freight services upon receiving positive recommendation. This contradicts findings from East, Hammond, Lomaxa and Robinson (2005) whose study highlights that positive 52 recommendations had a significant corresponding impact on intention to use the recommended product. This difference could be attributed to fact that intention to give positive recommendation was found to be low in this study. The implication of this is that WOM communication is not a sufficient driver of uptake of SGR freight services. Future purchase behaviour was determined by buying intention which was defined as ' clearing agents voluntarily nominating cargo to be transported using SGR freight services in the next year' . Responses in this section indicated that there were more clearing agents that did not intend to use SGR freight services in the next year than those that did. Another important observation was that intention to use SGR freight services in the future was higher among clearing agents currently not using the service. This could be an indicator that repurchase intentions amongst existing customers are more likely driven by other factors like service quality. A correlation analysis between WOM communication and market performance of SGR freight services as detetmined by future buying intention among clearing agents yielded a moderate positive relationship between the two variables. This is consistent with findings from Buttle (1998) that states that WOM influences behavioural intentions and behaviour. The model explains 59.3% of the variance in use ofSGR freight services. Other studies highlight factors that may explain the variance including interpersonal factors such as senders' expertise and the strength of the message (Sweeney et al. 20 14). The implication of this is that in addition to service quality and social influence from WOM communication, SGR freight services would have to determine other factors influencing future buying intention. Improving performance ofthese two variables would however positively impact market performance. 5.2.3 Service quality dimensions most likely to influence market performance of SGR freight services as determined by buying intention The third objective of the study sought to establish the service quality dimensions that are most likely to influence market performance of SGR freight services as determined by buying intention of the services by clearing agents. From the clearing agents perspective, the importance of service quality dimensions in order of importance were determined to be responsiveness (willingness to help customers and provide prompt suppmt), assurance (knowledge and courtesy of employees 53 and their ability to convey tmst and confidence), reliability (ability to perform the promised services accurately and dependably), tangibles (appearance of physical factors such as equipment, facilities and personnel) and lastly empathy (providing individual attention and care to customers). A binary logistic regression was used to determine the strength of the relationships. The model yielded the overall observation that improvement in service quality across all dimensions would result in an increase in market performance of SGR freight services as dete1mined by intention to buy. This is consistent with findings by several authors who highlight that there is a positive relationship between service quality and customers' willingness to recommend and buy a company or product (Cliceres & Paparoidamis, 2004; Choudhury, 2014 ). Only 8% of influence to buy SGR freight services was explained by the model. This could be attributed to the fact that relational variables were not included, these would provide evidence of links to other variables such as service quality, brand reputation and loyalty (Butt, Shah, & Iqbal, 2016). This is further consistent with findings from Pavlou (2003) who states that increase in service quality alone does not necessarily result in the higher purchase levels. All in all, tangibles and responsiveness were dete1mined to be the largest sources of influence in this model. This means that SGR freight services can increase market performance if they perform better in the tangibles and responsiveness dimensions. 5.3 Conclusion The study dete1mined that service quality has a positive relationship with market performance as determined by intention to buy SGR freight services from a clearing agent perspective. The results gave some validity to the Theory of Planned Behaviour in understanding intention to purchase SGR freight services. The direct measures were; for attitudinal beliefs perceived service quality, for subjective norm social influence of WOM communication and for perceived behavioural control customers ' judgement about the extent to which their decision is influenced by service quality dimensions. For attitudinal beliefs (perceived service quality), the study findings revealed that disconfi1mation was negative for all dimensions meaning that perception of outcomes for the service fell shmt of 54 expectations. Dissonance levels were highest in the dimension responsiveness followed by reliability and lowest in tangibility. The data also illustrated that customers have highest expectations in the parameters employees have support to do their job well followed by they are informed when a service will occur and third that they are served by employees who understand their needs. An analysis of the adopted SERVQUAL scale suggests that customers distinguish two dimensions of service quality in the case of SGR freight services in Kenya namely accessibility & effectiveness and service encounters. For the subjective norm (social pressure) - influence of WOM communication, the study detennined that there were low levels of willingness to recommend and give positive reviews of SGR freight services. Further, results highlight that more clearing agents indicated that they are unlikely to be influenced to use SGR freight services upon receiving positive recommendation and that intention to use SGR freight services in the future was generally low but higher among clearing agents currently not using the service. Despite the results from self-repmts from clearing agents, a coiTelation analysis between WOM communication and future purchase intention for SGR freight services among clearing agents yielded a moderate positive relationship between the two variables indicating that there is social influence from positive WOM recommendation on market perfmmance of SGR freight services . . These factors lead to conclude that: • WOM communication is not a sufficient driver of uptake of SGR freight services. • While WOM communication influences intention to use SGR freight services, other factors such as service quality play a role in this relationship. For perceived behavioural control which dete1mines the influence by factors out of respondents control, the study dete1mined that improvement in service quality across all dimensions would result in an increase in use of SGR freight services. The results from the self-reports from clearing agents highlight that the service quality dimensions in order of importance were responsiveness, assurance, reliability, tangibles and lastly empathy. It is however important to note that the dimensions that were determined to have the largest sources of influence on use of SGR freight services were tangibles and responsiveness. 55 5.4 Recommendations and Management strategies Service quality is a highly reviewed topic in service marketing literature with studies highlighting the need to optimally deploy resources to improve service quality in the areas that likely to lead to improvement in market competitiveness. The study presents recommendations in te1ms of managerial and policy implications. 5.4.1 Managerial implications Management should focus and draw their service improvement strategies from the dimensions that were detennined to have the largest source of influence on use of SGR freight services namely tangibles and responsiveness. Further focus should be placed on the dimensions as distinguished by customers namely accessibility & effectiveness and service encounters. It is recommended that the organization should ensure sufficient and up to date equipment to avoid delays that may be caused due to shortage of equipment. Further, investment in infrastructure to connect the p011 to key routes should be considered. Customers wish to be kept inf01med on the status of their service request and receive prompt service from employees who are willing to help and respond to requests; the organization should therefore train frontline staff to enable them assist customers and provide them with timely information. Focus on service attitude including courtesy, etiquette and communication skills is also necessary to achieve gains in this area. There is also opportunity for the organization to recognize customers as co-creators of the service and provide them with training on how best to use a service to mitigate against dysfunctional behaviour during service encounters (Sweeney, Soutar, & Mazzarol, 2014). The study also recommends that focus is placed on streamlining processes and further investment made in updating systems to enable the organization better process transactions and track service levels and complaints. 5.4.2 Policy implications In order to drive market performance and in tum revenue generation of SGR freight services, policy makers should focus on strategies that will drive product performance, service performance and customer value. Investment in business process reengineering, service delivery systems and 56 interoperability amongst the govemmental agencies involved in delivering this service shall be key towards achieving this goal. 5.5 Limitations of the study The study was subject to a number of limitations. Customer expectations and perceptions were determined from self-repmts from clearing agents and are by their nature subjective and constantly changing. The findings are therefore restricted to clearing agents in Kenya. Further, the study was cross-sectional in nature and generalized to the given period. This study focused on market performance from an intention to buy perspective. Other factors such as increasing reputation, preferences and satisfaction were not included in the scope of the study. Lastly, the two models; WOM communication as relates to use of SGR freight services and service quality as relates to use of SGR freight services, were assessed in isolation and relational variables such as customer influence, brand reputation and previous expeiience not included in the study. 5.6 Areas of further research The results of this study are consistent with previous findings and adds value to service marketing literature by providing evidence of the relationship between service quality and market performance for SGR (train) freight services in Kenya. 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