Determinants of switching intention in the electricity markets - An integrated structural model approach |
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| Institution: | 1. School of Business and Law, Edith Cowan University, 6027, Joondalup, WA, Australia;2. School of Economics, Finance and Marketing, RMIT University, 3000, Victoria, Australia;1. The Graduate School of Business Administration, Bar-Ilan University, Ramat-Gan, 5290002, Israel;2. The College of Law and Business, Ben Gurion 26, Ramat Gan, Israel;3. Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, 6997801, Israel;1. Hasselt University, Faculty of Business Economics, Department Marketing & Strategy, Martelarenlaan 42, 3500, Hasselt, Belgium;2. Vrije Universiteit Brussel, Faculty of Social Sciences & Solvay Business School, Department of Business, Marketing & Consumer Behaviour, Pleinlaan 2, 1050, Brussels, Belgium;3. Fairfield University, Charles F. Dolan School of Business, Department of Marketing, 1073 North Benson Road, Fairfield, CT, 06824-5195, USA;1. Energy Environment Policy and Technology, Graduate School of Energy and Environment (KU-KIST Green School), Korea University, 145 Anam-ro, Sungbuk-gu, Seoul, Republic of Korea;2. Policy Department, Korea Institute of Science and Technology, 5, Hwarang-ro 14-gil, Seongbuk-gu, Seoul, 02792, Republic of Korea;3. Department of Industrial and Management Systems Engineering, Department of Big Data Analytics, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin, Gyeonggi, 17104, Republic of Korea;4. College of Business, Gachon University, 1342 Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, 13120, Republic of Korea;5. Division of Data and Information Sciences (Major of Big Data Convergence), Pukyong National University, 45, Yongso-ro, Nam-gu, Busan, 48513, Republic of Korea |
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| Abstract: | This study adopts an integrated approach and combines the theory of planned behavior and push-pull theory to unpack the antecedents of customer switching intention in a contextual setting (Western Australia) that has a regulated electricity market. Partial least squares structural equation modeling was used to analyze data from a survey of 405 retail electricity consumers, which reveals that perceived relative price, electronic word-of-mouth, customer-based reputation of a service provider, past switching experience, and subjective norms significantly influence attitude toward switching and switching intention. Our findings contribute to the literature on retail electricity markets by showing the importance of customer-based reputation and positive electronic word-of-mouth in shaping consumers’ attitude and intention toward switching their electricity providers. The results also provide insights for electricity retailers to design better offerings and control customer switching. |
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| Keywords: | Switching behavior Push-pull theory Electricity retail market Push factors Pull factors Electronic word-of-mouth Attitude |
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