Int. J. Mobile Communications, Vol. 10

Int. J. Mobile Communications, Vol. 10, No. 4, 2012 Copyright © 2012 Inderscience Enterprises Ltd.An empirical study of consumer switching behaviour

Abstract: This study attempts to investigate the factors infl uencing consumer

switching behaviour towards mobile shopping. The Push-Pull-Mooring is extrapolated to delineate consumer switching behaviours towards mobile shopping.Our fi ndings indicate that mooring forces, trust, privacy and security and switching cost, have the strongest effect on switching intentions. However, the effects of pull forces such as alternative attractiveness and peer infl uence on switching intentions are stronger than those of push forces such as inconvenience. These fi ndings will aid mobile service providers, online marketers and companies in understanding what factors affect consumer behavioural intention to switch to mobile shopping.

Keywords: mobile shopping, switching behaviour, Push-Pull-Mooring

Reference to this paper should be made as follows: Lai, J-Y., Debbarma, S. and

Ulhas, K.R. (2012) ‘An empirical study of consumer switching behaviour towards

mobile shopping: a Push-Pull-Mooring model, Int. J. Mobile Communications,

Vol. 10, No. 4, pp.386–404.Biographical notes: Jung-Yu Lai is a faculty member of the Institute of Technology Management at the National Chung Hsing University (NCHU) in Taiwan. His current research interests include enterprise resource planning, e-business, e-learning, service quality management, technology management and knowledge management. He has publications in Computers in Human behaviour, Electronic Library, Information & Management, Information Systems Frontiers, International Journal of Human-Computer Studies, Industrial Marketing Management, International Journal of Mobile Communications, Journal of Systems & Software, Journal of the American Society for Information Science and Technology, Online Information Review and Technovation.Sutapa Debbarma has acquired her MBA from National Chung Hsing University (NCHU), Taiwan. She has received her Bachelor’s and Master’s degree in Electronics and telecommunication engineering at Pune University, India. Her current research interests include technology marketing, international marketing and telecommunication engineering.

An empirical study of consumer switching behaviour towards mobile shopping 387 Khire Rushikesh Ulhas is a PhD. student of the Institute of Management of Technology at the National Chung Hsing University (NCHU),Taiwan. He received his Bachelor’s and Master’s degree in Electrical engineering at Pune University, India. He also has received master’s degree in Technology Management from Institute of Management of Technology at the National Chung Hsing University (NCHU) in Taiwan. His current research interests include technology management, service design & management and e-learning.

• Introduction

As an extension of e-commerce, mobile commerce (m-commerce) is considered a separate channel that can deliver value by offering convenience and accessibility anywhere, anytime (Balasubramanian et al., 2002; Ko et al., 2009). Very high penetration rates of mobile phones, combined with the intimate nature of mobile phone use (most users perceive the mobile device as an extension of their identity), provide opportunities for the ongoing development and commercialisation of more sophisticated mobile services (O’Doherty et al., 2010).Mobile shopping plays an integral role in the daily routine of many users. It empowers shoppers with the ability to gather information on the spot from multiple sources, check on product availability, special offers and alter their selection at any point along the path to purchase. Thus, the consumer shopping modality is quickly and decisively changing from traditional shopping and PC-based online shopping to mobile shopping (Ali et al., 2011; Butcher, 2011; Sharma, 2011). Because consumers across all age groups want to use mobile devices not only as a search tool for shopping decisions but also to make payments directly from their device while in a store has led to the exponential growth of m-commerce (Oracle Inc., 2011). Obviously, the rate of adoption of mobile devices as shopping platforms is impressive, outpacing the initial rate of adoption for personal computers as a shopping channel (Ali et al., 2011). Hence, investigation of consumer switching intentions towards mobile shopping has assumed new importance. To understand switching behaviour in the mobile shopping context, the nature of forces encountered by consumers must be understood (Lai et al., 2011). Therefore, the primary objective of the study is the determination of critical antecedents, their relationships and their role in consumer switching intentions towards mobile shopping.Along with switching behaviour, the impact of social and cultural factors on mobile technology adoption still requires much research (Crabbe et al., 2009; Kofod-Petersen et al., 2010; Liu et al., 2011). Hence, a substantive-theory-based research on m-commerce is necessary. Consumers switching to mobile shopping may be viewed as analogous to switching between shopping modes and, hence, the switching behaviour can be treated as a migration.Switching behaviour may thus be analysed using a human migration model frequently used by scholars to explain switching behaviour (Hou et al., 2011). The PPM model, taken from the migration literature (Bansal et al., 2005), appears to be a promising approach to modelling consumer switching behaviour towards mobile shopping and examining the factors infl uencing consumer switching behaviours as well as their relationships.The present work answers two key questions: What are the factors that infl uence consumers’ switching intentions towards mobile shopping and ultimately behavioural intentions? What theoretical framework can be used to clarify the underlying factors in investigating consumer switching behaviours in the mobile shopping context? The

388 J-Y. Lai et al.remainder of this paper is organised as follows. The next section provides the theoretical background including a brief review of the PPM model in migration as well as in the mobile shopping context. In the third section, we present our research model and hypotheses. In the fourth section, the research methodology and analysis of the model are described. Section 5 presents the discussions of this study. The fi nal section consists of conclusions along with a discussion of the managerial implications of our study, its limitations and an outline of future research directions.

• Theoretical background

2.1 Migration Migration is referred as the movement of a person between two places for a certain period of time (Boyle and Halfacree, 1999). Migration can be classifi ed into two types, namely temporary and permanent. Temporary migrants return to their origin after a certain time interval whereas permanent migrants do not (Hou et al., 2009). Needless to say, a permanent transition to mobile shopping is unlikely under current conditions.However, temporary migration and contemporary mobile shopping appear to be analogous, if ‘switching’ is defi ned as the frequency of repetitive purchase through the mobile channels. The literature also classifi es migration into voluntary and involuntary migration (Gebre, 2002). Voluntary migrants freely decide to migrate without any formal constraints. Refugees or involuntary migrants have no choice but to migrate owing to constraints such as war, persecution, or famine (Boyle and Halfacree, 1999). Obviously, mobile shopping could be considered a voluntary migration from traditional and online shopping to mobile shopping.

2.2 Push-Pull-Mooring The Push-Pull-Mooring (PPM) paradigm suggests that a migrant’s decision to move from one area to another is affected by push, pull and mooring factors (Zhang et al., 2008). Push factors are negative factors at the origin that push people away, whereas pull factors are positive factors at the destination that attract individuals to a destination (Bansal et al., 2005; Cheng et al., 2009). For instance, push factors include a lack of work opportunities, a decline in natural resources or the prices paid for them and natural disasters, whereas pull factors include better development and work opportunities, higher income and comfortable climate (Bansal et al., 2005). Owing to the complex nature of migration decisions, push and pull factors by themselves do not adequately describe migration behaviour; intervening variables are required (Zhang et al., 2008). Therefore, migration researchers have introduced the concept of mooring forces as ‘intervening’ and ‘personal’ factors consisting of personal, social and cultural forces that can either hold potential migrants to their place of origin or facilitate the movement of migrants to a new destination (Bansal et al., 2005). Since the PPM model originated in the fi eld of migration studies, modifi cation of its framework by unifying the most commonly used predictors is required to enhance performance and contextual fi tting when applying the PPM to other fi elds (Bansal et al., 2005; Cheng et al., 2009; Chiu et al., 2011; Hou et al., 2009, 2011; Lui, 2005; Ye and Potter, 2007; Zhang et al., 2008). This study summarises several prior studies exploring consumer behaviour in online contexts that have used the PPM model and unifi ed its factors (Table 1).

An empirical study of consumer switching behaviour towards mobile shopping 389

• Research model and Hypothesis

3.1 Push effects Push factors are negative factors that motivate people to switch from the origin (Bansal et al., 2005). Similarly, in this study, push factors represent the disadvantages of other shopping channels such as electronic shopping (e-shopping) and traditional shopping. E-shopping offers consumers a higher level of convenience and saves time and effort over traditional shopping (Liu et al., 2011; Verhoef and Langerak, 2001). However, online shopping using PCs has two constraints. First, users must sit in front of them. Second, even notebook PCs have to load software, dial into and connect with a network service provider and await completion of the connection with the server before they can launch internet applications.People who require real-time action and have satisfi ed time-critical needs require prompt and to-the-point interactions (Sadeh, 2002) and will not be satisfi ed with traditional or e-shopping modality. In case of online shopping, low-speed connections, bothersome software bugs and poorly constructed subroutines will reduce perceived technical quality. Moreover, interface complexity and information content and reliability may be questionable. Furthermore, both traditional and online shopping are constrained by limited connectivity and access, reducing the opportunity to shop. Thus, consumers encountering inconvenience are more likely to be pushed away from existing shopping modalities, traditional shopping and online shopping and generate an intention to switch to mobile shopping. Hence, we hypothesise (Figure 1): Table 1 Prior PPM research Predictors for switching Context References Push Pull Mooring Quality, Satisfaction, Value, Trust, Commitment, High price perception Alternative attractiveness Attitude, Subjective norms, switching costs, prior switching behaviour, variety seeking Service provider switching Bansal et al.

(2005)

Dissatisfaction Attraction, Peer infl uence Switching cost Switching intentions in social networking sites Cheng et al.

(2009)

Satisfaction Alternative attractiveness Sunk cost Blogs service switching Zhang et al.

(2008)

Enjoyment, satisfaction, participation Alternative attractiveness Switching cost, social relationship, prior experience Switching between online games Hou et al.

(2009, 2011)

Habit, breadth of use, satisfaction Relative advantage, perceived ease of use Subjective norms, risk aversion, switching cost Personal information technology Ye and Potter

(2007)

Self-effi cacy Alternative attractiveness Switching cost, multichannel integration Multichannel service switching Chiu et al.

(2011)