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Hsieh, J.C.; Lin, S.; , . Consumption Motivation at High-Speed Rail Stations. Encyclopedia. Available online: https://encyclopedia.pub/entry/22274 (accessed on 28 March 2024).
Hsieh JC, Lin S,  . Consumption Motivation at High-Speed Rail Stations. Encyclopedia. Available at: https://encyclopedia.pub/entry/22274. Accessed March 28, 2024.
Hsieh, Jing Chzi, Sheng-Hau Lin,  . "Consumption Motivation at High-Speed Rail Stations" Encyclopedia, https://encyclopedia.pub/entry/22274 (accessed March 28, 2024).
Hsieh, J.C., Lin, S., & , . (2022, April 26). Consumption Motivation at High-Speed Rail Stations. In Encyclopedia. https://encyclopedia.pub/entry/22274
Hsieh, Jing Chzi, et al. "Consumption Motivation at High-Speed Rail Stations." Encyclopedia. Web. 26 April, 2022.
Consumption Motivation at High-Speed Rail Stations
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Exploring passengers’ consumption motivation can provide the basis for arranging commercial activities in high-speed rail (HSR) stations to generate more revenue for operations. The passenger traffic at five major HSR stations in Taiwan were evaluated. Based on the results of decision-making trial and evaluation laboratory (DEMATEL) and DEMATEL-based on the analytical network process methods, it is shown that station attributes and consumption environment attributes are key factors that impact product attributes. Moreover, store location, commercial activities offered, product diversity, time pressure, and service convenience have a “cause” characteristic and, therefore, should be focused on when deploying commercial services at HSR stations.

high-speed rail stations consumption motivation MADM model DEMATEL DANP modified VIKOR

1. Introduction

High-speed rail (HSR) are a popular transportation facility in many countries around the world, including Japan, France, Germany, Spain, Belgium, the United Kingdom, Switzerland, the United States, South Korea, Italy, Taiwan, China, Saudi Arabia, and the Netherlands. It is characterized by safety, comfort and efficiency. Emerging countries, such as Iran, Morocco, and Mexico, are also actively building high-speed rail networks [1][2]. The construction of a HSR network increases accessibility between different cities, causing a change in population distribution and industrial structure [3]. From the perspective of urban design, transportation facilities are seen as transcending the functional elements that ensure efficient traffic flow. Streets, railway stations, and bus stops can all be regarded as important components of an area [4]. However, the development of HSR network is more expensive than building a traditional railway network due to the higher-quality infrastructure required [1]. Failure to properly manage this infrastructure will result in HSR stations remaining idle and could lead to bankruptcy. Policymakers are trying to devise ways to generate revenue from sources other than fares to promote sustainable operation of HSRs. Among them, providing business activities or services is an important strategy [5].
A railway station is an attractive location for commercial purposes, providing shopping, business, and leisure opportunities to both passengers and residents. Therefore, rail companies can generate additional revenue by operating commercial and retail areas. Currently, HSR operations are mainly funded by fare income, followed by income from ancillary commercial facilities. For example, the JR West line in Japan had a total operating income of about 158.2 billion Japanese Yen in 2020, to which affiliated commercial facilities contributed 574.8 billion yen (about 38% of the total operating income) [6]. To achieve sustainable operations, the positioning and installation of commercial facilities in the train stations are important [7]. Exploring rail passengers’ consumption behavior at HSR stations is an important means to provide services based on user perceptions and expectations [8]. There is an abundance of studies on commercial facilities and consumer behavior at airports [9][10][11][12][13][14][15], but there are few that explore passengers’ consumption behavior at HSR stations, despite it being an important research issue. This study aims to fill this gap on the consumption motivations of passengers at HSR stations.
Previous studies on passengers’ consumption behavior in transportation facilities have mostly used statistical regression analysis [12][13][15][16], Pearson correlation test [9], or modified grey correlation analysis [10]. However, as consumption motivations are affected by various qualitative or quantitative factors, multiple-attribute decision making (MADM) models are increasingly being used [17]. Among the many MADM models, analytic hierarchy process (AHP), developed by Saaty [18], is a popular method for analyzing issues in transport infrastructure projects [19]; it has been utilized to explore passenger satisfaction in urban multi-mode public transportation in Ningbo, China [20], and factors of customer happiness in authorized workshops [21]. However, traditional AHP cannot solve the problem of complex influential relationships among the different motivations [22]. Although the analytical network process (ANP), improved by Saaty [23], relaxes the assumption on the construction of a relationship network, the influential matrix still lacks a reliable foundation [24]. Of late, more and more studies have utilized the advanced decision-making trial and evaluation laboratory (DEMATEL) to explore the complex influence relationships in issues related to determinants of consumption, including online consumption [25], airline passenger satisfaction [26], green marketing [27], and second-hand clothing purchase motivation [28].

2. Constructing a Framework for Exploring Passengers’ Consumption Motivations at HSR Stations

Public transportation nodes, especially railway stations, have become the focus in urban land planning. A rail station is a special facility for passengers to embark and disembark, wait, or transfer using several means, such as platforms, floors, escalators, automatic ticketing systems, and transportation equipment [29]. A rail station can be said to have five functions: connect catchment areas and transportation networks, support the transfer of passengers or cargo between transportation modes, promote commercial use of real estate, provide a public space, and contribute to the identity of the surrounding area [30]. Through public transport operators, it can increase the utilization rate of its services by improving the quality of services provided [31]. Ghosh et al. [32] pointed out that platforms are also an important part of a rail station. Individuals use a variety of platform-based convenience facilities, such as refreshment stalls, ATMs, toilets, cloakrooms, and waiting rooms. Retail activities also play a vital role at the station and can help utilize the space effectively by providing shopping facilities to passengers [33][34].
As a representative example of a HSR, the West Japan Railway Company (JR west) integrates commercial facilities into its rail stations for optimizing the station layout, thereby increasing passenger convenience and providing additional value [35]. Kim et al. [36] proposed that a HSR station is not only a transportation hub, but also integrates shopping, dining, business, and leisure activity centers for attracting more passengers. From the passengers’ perspective, Ojha [37] indicated that the most important amenities on India’s railway stations are the food and beverage facilities. Be it a traditional railway station or a HSR station, its functions have expanded from simply giving a ride to diversified functions such as shopping or dining for more convenience [30].
Selecting a suitable location within the HSR station to configure commercial services is an issue in the design of a rail station. Three dimensions—station attributes (D1), product attributes (D2), and environment attributes (D3)—are used for evaluating the framework to explore passengers’ consumption motivations at a HSR station (Table 1).
Table 1. Framework for passenger consumption motivation at HSR stations.
Dimension Criteria Definitions Cited Literature
Station attributes (D1) Station scale (C1) The scale of HSR stations [14][38][39]
Store location (C2) Location of stores in HSR stations [12][14][38][39]
Commercial activities offered (C3) Commercial activities provided in HSR stations, such as dining, shopping, and entertainment facilities [13][40][41]
Product attributes (D2) Product diversity (C4) The variety of products offered by the shops in the HSR station [12][42][43][44]
Product quality (C5) The quality of the products provided by the stores in the HSR station [42][44][45]
Product retail price (C6) The prices of the products sold by the shops in the HSR stations are reasonable [16][42][44][46]
Brand name (C7) Whether the brands sold in the HSR stations are well-known to passengers [10][42][44]
Consumption environment attributes (D3) Environment (C8) The ambient atmosphere of the shops in the HSR stations, such as cleanliness, lighting, or temperature [11][45][47][48]
Time pressure (C9) The free time available from the time a passenger enters the HSR station till the time of embarking. If there is too little free time, there will be a time pressure. [15][16][49][50]
Service quality (C10) The service quality of the service staff in the stores in HSR stations and whether the quality is high or low [11][12][44][49][51]
Service convenience (C11) Convenience of consumption by passengers in HSR stations, such as the convenience of obtaining products, making payments, and deciding the type of business activities to consume [44][47][52][53]
The location of the stores provides unique competitive advantages for the stores and has important implications for business revenue [54]. Unlike large shopping malls or department stores, special consideration has to be given to the relationship among available scale space, accessibility, and types of commercial activities provided at rail stations due to the limited space available [55]. Hence, station attributes (D1) are selected as one dimension. Moreover, the attributes related to product and consumption environment must also be carefully considered. While designing a mall atmosphere, product and service classification based on customer preferences is very important, especially as satisfying consumers’ hedonic and utilitarian values will promote spending [42]. Wagner and Rudolph [56] pointed out that non-food shopping focuses more on retailers’ store atmosphere and service convenience, while food shopping focuses more on the product itself. Hence, increasing the consumption efficiency can increase spending whether it is food or non-food shopping. With the rapid developments in technology, customers now interact with technology to create more service results while non-aviation-related activities such as shopping and dining in the airport have increased at the same time [47]. Hence, product attributes (D2) and environment attributes (D3) come into the picture. The selected criteria in each dimension are described as follows.

2.1. Station Attributes (D1)

An appropriate scale of transportation facilities allows the setting up of a certain number of commercial facilities, which gives passengers the illusion that they are in a shopping center so they increase their spending and improve the retail revenue of the facility [14][38]. Apart from the routine eating and shopping facilities, entertainment activities can also be added [13]. An abundance of commercial facilities, such as hotels, department stores, theaters, and museums can also be provided to increase the consumption of tourists [40]. Stores should be located in the most accessible part for passengers according to the level of turnover. If a store is located in a corner or a passageway that is used less frequently, it will reduce the consumption motivation of passengers [12][14]. In transportation facilities such as airports, the provision of a wider range of retail and catering options has also proven to be an important factor in increasing passenger satisfaction and airport service quality [57]. Based on the above, this study includes three criteria in the dimension of station characteristics (D1): station scale (C1), store location (C2), and commercial activities provided (C3).

2.2. Product Attributes (D2)

In consumer behavior, providing multiple brands and high-quality products at competitive prices increases the satisfaction of shoppers and promotes shopping and exploration [42]. Geuens et al. [43] mentioned that diverse types of products sold in transportation facilities that include both internationally-known and locally-known brands can trigger the consumption motivation of passengers. Some studies also indicate that brand name has a significant impact on the consumption satisfaction of passengers [10]. Product discounts also increase passengers’ consumption motivation [46]. Lu [44] has shown that product quality, price, and brand reputation are critical in affecting consumption motivation in transportation facilities. Based on the above, this study includes four criteria in the dimension of product attribute (D2): product diversity (C4), product quality (C5), product retail price (C6), and brand name (C7).

2.3. Consumption Environment Attributes (D3)

Time and emotion affect passenger consumption in transportation facilities. Passengers are more concerned about convenience attributes, which involves how to easily and comfortably access the service environment and the availability and quality of convenience facilities and services provided [58]. Quality attributes in the physical environment are more important to operators [47]. Kesari and Atulkar [42] found that the use of bright attractive colors, lighting, cooling, cleanliness, fragrance, and luxurious seating produces a pleasant and exciting environment that allows consumers to relax. Rail stations can be designed in a way that reduces stress for passengers through the use of colors, lighting, temperature control, and decorative objects (real plants or art installations), thereby enhancing passengers’ consumption motivation [11][45][46][48]. Some studies have also shown that time pressure has a significantly negative impact on passengers’ consumption motivation [15][16][49][50], as they would be in a rush to catch their trains. Transportation facilities should provide more service personnel who provide high quality services to reduce the time pressure of passengers [44][52][53]. Good service quality by service personnel can also increase passengers’ excitement [49], which echoes the viewpoint that good service quality increases passenger satisfaction and motivation [9][11][44][51]. Based on the above, this study includes four criteria in this dimension: environment (C8), time pressure (C9), service quality (C10), and service convenience (C11).

References

  1. Almujibah, H.; Preston, J. The Total Social Costs of Constructing and Operating a High-Speed Rail Line Using a Case Study of the Riyadh-Dammam Corridor, Saudi Arabia. Front. Built Environ. 2019, 5, 79.
  2. Cheng, Y.-H. High-speed rail in Taiwan: New experience and issues for future development. Transp. Policy 2010, 17, 51–63.
  3. Garmendia, M.; Ribalaygua, C.; Ureña, J.M. High speed rail: Implication for cities. Cities 2012, 29, S26–S31.
  4. Brovarone, E.V. Design as if bus stops mattered: Exploring the potential role of public transport stops in the urban environment. Urban Des. Int. 2021, 26, 82–96.
  5. Abutaleb, A.; Mcdougall, K.; Basson, M.; Hassan, R.; Mahmood, M.N. Understanding Contextual Attractiveness Factors of Transit Orientated Shopping Mall Developments (Tosmds) for Shopping Mall Passengers on the Dubai Metro Red Line. Plan. Pract. Res. 2020, 36, 292–313.
  6. JR West Company. Financial Report. 2021. Available online: https://www.westjr.co.jp/company/ir/finance/results/ (accessed on 17 May 2021).
  7. Baron, N. Designing Paris Gare du Nord for pedestrians or for clients? New retail patterns as flow optimization strategies. Eur. Plan. Stud. 2019, 27, 618–637.
  8. Machado-León, J.L.; de Oña, R.; Baouni, T.; de Oña, J. Railway transit services in Algiers: Priority improvement actions based on users perceptions. Transp. Policy 2017, 53, 175–185.
  9. Chang, J.; Yang, B.-T.; Yu, C.-G. The moderating effect of salespersons’ selling behaviour on shopping motivation and satis-faction: Taiwan tourists in China. Tour. Manag. 2006, 27, 934–942.
  10. Perng, S.-W.; Chow, C.-C.; Liao, W.-C. Analysis of shopping preference and satisfaction with airport retailing products. J. Air Transp. Manag. 2010, 16, 279–283.
  11. Lin, Y.-H.; Chen, C.-F. Passengers’ shopping motivations and commercial activities at airports—The moderating effects of time pressure and impulse buying tendency. Tour. Manag. 2013, 36, 426–434.
  12. Sahak, S.Z.; Yusof, A.W.M.; Mudri, E.Y.A.; Saidin, S. The Effect of Retail Mix on Passengers Motivation to Shop at AirportTerminal Outlets. J. Int. Bus. Econ. Entrep. 2018, 3, 30–36.
  13. Tseng, W.-C.; Wu, C.-L. A choice model of airline passengers’ spending behaviour in the airport terminal. Transp. Plan. Technol. 2019, 42, 380–390.
  14. Chen, Y.; Wu, C.-L.; Koo, T.T.R.; Douglas, I. Determinants of airport retail revenue: A review of literature. Transp. Rev. 2020, 40, 479–505.
  15. Lee, J.I.; Ren, T.; Park, J. Investigating travelers’ multi-impulse buying behavior in airport duty-free shopping for Chinese traveler: Intrinsic and extrinsic motivations. J. Air Transp. Manag. 2021, 92, 102023.
  16. Lin, W.-T.; Chen, C.-Y. Shopping Satisfaction at Airport Duty-Free Stores: A Cross-Cultural Comparison. J. Hosp. Mark. Manag. 2013, 22, 47–66.
  17. Yıldız, N.; Tüysüz, N. A hybrid multi-criteria decision making approach for strategic retail location investment: Application to Turkish food retailing. Socio-Econ. Plan. Sci. 2019, 68, 100619.
  18. Saaty, T.L. The Analytic Hierarchy Process; McGraw-Hill: New York, NY, USA, 1980.
  19. Broniewicz, E.; Ogrodnik, K. Multi-criteria analysis of transport infrastructure projects. Transp. Res. Part D Transp. Environ. 2020, 83, 102351.
  20. Zhang, X.; Liu, H.; Xu, M.; Mao, C.; Shi, J.; Meng, G.; Wu, J. Evaluation of passenger satisfaction of urban multi-mode public transport. PLoS ONE 2020, 15, e0241004.
  21. Kumar, A. Analysing the drivers of customer happiness at authorized workshops and improving retention. J. Retail. Consum. Serv. 2021, 62, 102619.
  22. Tzeng, G.-H.; Shen, K.-Y. New Concepts and Trends of Hybrid Multiple Criteria Decision Making; CRC Press: Boca Raton, FL, USA, 2017.
  23. Saaty, T.L. The Analytic Network Process; RWS Publications Press: Pittsburgh, PA, USA, 1996.
  24. Gölcük, I.; Baykasoğlu, A. An analysis of DEMATEL approaches for criteria interaction handling within ANP. Expert Syst. Appl. 2016, 46, 346–366.
  25. Chen, H.-M.; Wu, C.-H.; Tsai, S.-B.; Yu, J.; Wang, J.; Zheng, Y. Exploring key factors in online shopping with a hybrid model. SpringerPlus 2016, 5, 2046.
  26. Perçin, S. Evaluating airline service quality using a combined fuzzy decision-making approach. J. Air Transp. Manag. 2018, 68, 48–60.
  27. Tsai, P.-H.; Lin, G.-Y.; Zheng, Y.-L.; Chen, Y.-C.; Chen, P.-Z.; Su, Z.-C. Exploring the effect of Starbucks’ green marketing on consumers’ purchase decisions from consumers’ perspective. J. Retail. Consum. Serv. 2020, 56, 102162.
  28. Medalla, M.E.F.; Yamagishi, K.D.; Tiu, A.M.C.; Tanaid, R.A.B.; Abellana, D.P.M.; Caballes, S.A.A.; Jabilles, E.M.Y.; Selerio, E.F., Jr.; Bongo, M.F.; Ocampo, L.A. Relationship mapping of consumer buying behavior antecedents of secondhand clothing with fuzzy DEMATEL. J. Manag. Anal. 2021, 8, 530–568.
  29. Vuchic, V.R. Urban Transit: Operations, Planning and Economics; Wiley: Hoboken, NJ, USA, 2005.
  30. Zemp, S.; Stauffacher, M.; Lang, D.J.; Scholz, R.W. Classifying railway stations for strategic transport and land use planning: Context matters! J. Transp. Geogr. 2011, 19, 670–679.
  31. Guirao, B.; García-Pastor, A.; López-Lambas, M.E. The importance of service quality attributes in public transportation: Narrowing the gap between scientific research and practitioners’ needs. Transp. Policy 2016, 49, 68–77.
  32. Ghosh, P.; Ojha, M.K.; Geetika. Determining passenger satisfaction out of platform-based amenities: A study of Kanpur Central Railway Station. Transp. Policy 2017, 60, 108–118.
  33. Xiao-Rong, L.; Hai-Xiao, P. The effects of the integration of metro station and mega-multi-mall on consumers’ activities: A case study of Shanghai. Transp. Res. Procedia 2017, 25, 2574–2582.
  34. Siewwuttanagul, S.; Inohae, T. Spatio-temporal Retail Competition Factors Accessibility in Hakata Station, Japan. In Introduction to the Lecture Notes in Mobility; Weerawat, W., Kirawanich, P., Fraszczyk, A., Marinov, M., Eds.; Springer: Singapore, 2021; pp. 167–184.
  35. Tsuji, A. Developing Station Commercial Facilities to Increase Line Section Value. Jpn. Railw. Trans. Rev. 2010, 56, 14–21.
  36. Kim, H.; Sultana, S.; Weber, J. A geographic assessment of the economic development impact of Korean high-speed rail stations. Transp. Policy 2018, 66, 127–1137.
  37. Ojha, M.K. Quality of service delivery at railway platforms: A case of Allahabad junction railway station. Case Stud. Transp. Policy 2020, 8, 1087–1095.
  38. Volkova, N. Determinants of Retail Revenue for Today’s Airports. German Airport Performance (GAP) Project; Berlin School of Economics: Berlin, Germany, 2009.
  39. Wu, C.-L.; Chen, Y. Effects of passenger characteristics and terminal layout on airport retail revenue: An agent-based simulation approach. Transp. Plan. Technol. 2019, 42, 167–186.
  40. Ando, K. Japan’s Rail Stations. Jpn. Railw. Transp. Rev. 2010, 56, 26–35.
  41. Ünder, Ü.; Atalık, Ö. Investigating Airport Shoppers’ Buying Behaviors and Satisfaction at Duty Free Shops: Impact of Demographic and Travel Related Factors. Transp. Logist. 2020, 20, 45–60.
  42. Kesari, B.; Atulkar, S. Satisfaction of mall shoppers: A study on perceived utilitarian and hedonic shopping values. J. Retail. Consum. Serv. 2016, 31, 22–31.
  43. Geuens, M.; Vantomme, D.; Brengman, M. Developing a typology of airport shoppers. Tour. Manag. 2004, 25, 615–622.
  44. Lu, J.-L. Investigating factors that influence passengers’ shopping intentions at airports—Evidence from Taiwan. J. Air Transp. Manag. 2014, 35, 72–77.
  45. Han, H.; Hyun, S.S. Investigating customers’ shopping behaviors at airport duty-free shops: Impact of shopping flow and alternative shopping malls’ attractiveness. Asia Pac. J. Tour. Res. 2018, 23, 627–638.
  46. Park, J.-W.; Choi, Y.-J.; Moon, W.-C. Investigating the effects of sales promotions on customer behavioral intentions at duty-free shops: An Incheon International Airport case study. J. Airl. Airpt. Manag. 2013, 3, 18–30.
  47. Hong, S.-J.; Choi, D.; Chae, J. Exploring different airport users’ service quality satisfaction between service providers and air travelers. J. Retail. Consum. Serv. 2020, 52, 101917.
  48. van den Oel, C.J.; Berkhof, F.W.; Derk, V.D. Consumer preferences in the design of airport passenger areas. J. Environ. Psychol. 2013, 36, 280–290.
  49. Sadikoglu, G. Modeling of the travelers’ shopping motivation and their buying behavior using fuzzy logic. Procedia Comput. Sci. 2017, 120, 805–811.
  50. Sohn, H.-K.; Lee, T.J. Tourists’ impulse buying behavior at duty-free shops: The moderating effects of time pressure and shopping involvement. J. Travel Tour. Mark. 2017, 34, 341–356.
  51. Park, J.-W.; Se-Yeon, J. Transfer passengers’ perceptions of airport service quality: A case study of Incheon international airport. Int. Bus. Res. 2011, 4, 75.
  52. Seiders, K.; Voss, G.B.; Grewal, D.; Godfrey, A.L. Do Satisfied Customers Buy More? Examining Moderating Influences in a Retailing Context. J. Mark. Manag. 2005, 69, 26–43.
  53. Chung, Y.-S.; Wu, C.-L.; Chiang, W.-E. Air passengers’ shopping motivation and information seeking behaviour. J. Air Transp. Manag. 2013, 27, 25–28.
  54. Lin, S.-H.; Hsu, C.-C.; Zhong, T.; He, X.; Li, J.-H.; Tzeng, G.-H.; Hsieh, J.-C. Exploring location determinants of Asia’s unique beverage shops based on a hybrid MADM model. Int. J. Strat. Prop. Manag. 2021, 25, 291–315.
  55. Cushman & Wakefield. Railway Retail in France and Southern Europe; Cushman & Wakefield: Paris, France, 2018.
  56. Wagner, T.; Rudolph, T. Towards a hierarchical theory of shopping motivation. J. Retail. Consum. Serv. 2010, 17, 415–429.
  57. Prentice, C.; Kadan, M. The role of airport service quality in airport and destination choice. J. Retail. Consum. Serv. 2019, 47, 40–48.
  58. Bezerra, G.C.; Gomes, C.F. The effects of service quality dimensions and passenger characteristics on passenger’s overall satisfaction with an airport. J. Air Transp. Manag. 2015, 44–45, 77–81.
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