ABSTRACT
Purpose: This study aims to examine the interconnectedness between investors' perceptions of assets and their behavioral factors with investment decisions during the COVID-19 pandemic in the real estate business in Pakistan. In this regard, this study predicted investment decisions using individuals' perceptions of the asset (perceived asset quality, perceived asset price and perceived asset value [PAV]),and behavioral biases (overconfidence [OC], herding [HD], disposition effect [DE] and risk aversion [RA]). Design/methodology/approach: This study used a survey-based instrument to gather a total of 189 usable samples. The sample data were analyzed using partial least square structural equation modeling. Findings: The findings of this study indicated that PAV, OC and HD significantly predicted the investment decision, whereas DE and RA had an insignificant impact on investment decisions in the real estate business. In addition, this study found that PAV is the most important factor to predict investment decisions in real estate during the COVID-19 crisis. Originality/value: The authors are certain that the study findings reinforce policy implications for regulators, policymakers and financial institutions. The study findings are also useful and relevant if the real estate sector experiences a crisis in the future. © 2023, Emerald Publishing Limited.
ABSTRACT
Usage of online teaching and learning platforms to support mobile or remote learning in higher education institutions have been widely utilised throughout the COVID-19 pandemic as movements were restricted, disallowing physical classes. Many agree with the functions and benefits of these online platforms. Thus, this study aims to analyse the determinants that would influence the acceptance and use of technology based on the UTAUT model for permanent adoption of the system. The results showed that performance expectancy, effort expectancy and facilitating condition have significant influences over behaviour intention to use the online systems, intention having influences on usage behaviour as well as hedonic motivations having mediating effects on the relationship between performance expectancy and facilitating condition with behaviour intention. Findings and implications of this study are discussed to assists the education industry. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Mobile grocery shopping has gained traction recently due to the COVID-19 pandemic. Hence, this study aims to investigate the antecedents that influence consumers’ buying intention through mobile grocery shopping. This was achieved through the use of a multi-perspective research model that includes the consumers’ positive and negative valences as well as consumer characteristics. Data was collected from 400 Malaysian consumers and analyzed using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) analysis. The finding of the study indicated the significant effects of positive valences (e.g., hedonic and utilitarian value) but not negative valences (e.g., privacy concern and security risk) on consumer buying intention through mobile grocery shopping. This study among the first to examine the intricacies of varying consumer characteristics in the context of mobile grocery shopping. The implications derived from the findings of this study are discussed. © 2022 International Association for Computer Information Systems.
ABSTRACT
Purpose - This study aims to simultaneously examine the influence of demographic. psychographic and situational factors on consumers' willingness to pay a price premium (WTPp) for robotic restaurants and to profile market segments based on consumers WTPp levels (positive, neutral and negative). Design/methodology/approach - Using an online survey, the data were gathered from a sample of 897 Thai consumers who had dined at a robotic restaurant in the past 12 months. Structural equation modeling, chi-square tests and the one-way analysis of variance were used for data analysis. Findings - Demographic (gender, age, income and marital status), psychographic (perceived advantages/disadvantages, personal innovativens and personality traits) and situational factors (perceived health risk and self-protection behavior) significantly influence consumers' WTPp for robotic restaurants. The positive price premium group differs significantly from the neutral and negative price premium groups in terms of demographic, psychographic and situational profiles. Practical implications - The findings of this study help restaurateurs target the correct customers and set up appropriate price fences to safeguard profits and maximize return on investment. Originality/value - This study contributes to the literature on technology-based services and hospitality by heeding the calls made by lvanov and Webster (2021) and providing much-nwded empirical evidence of possible changes in consumers' WTPp for robot-delivered services in restaurants due to COVID-19.