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Despite the immense popularity of WhatsApp, there needs to be more reliable and valid scales for identifying and measuring users' motivation behind frequent WhatsApp status updates. This study explores the underlying motivations of users in updating their WhatsApp statuses and develops a scale to measure them.

Following a mixed-method research design, data were obtained from WhatsApp users in India. The current research furnishes results from five studies, involving both qualitative and quantitative approaches.

The results uncover seven unique motivations of users for keeping WhatsApp status, namely: social good, attention seeking, social relations, expressing views, life updates, inspiration and entertainment. Additionally, the empirical findings demonstrate the effects of the above dimensions on the positive and negative emotions of users.

This research is a pioneering effort in developing and validating a scale on WhatsApp status motivation construct. Key managerial and scholarly implications of the findings arising from this research are also discussed.

The purpose of this research is to investigate the influence of psychological contract violation (PCV) on service quality and perceived value, and consequently on users positive word of mouth intention towards mobile shopping applications. The role of personalization as a moderator is further investigated.

A descriptive research approach was adopted, and responses were gathered from 252 mobile shopping application users in India, using an online survey. The variance-based partial least square structural equation modelling approach was opted for analysing the research model.

The results showed the deleterious effects of PCV on service quality and perceived value. The findings further confirm the significant positive impact of service quality and perceived value on the positive word of mouth intention of users. The role of personalization in mitigating the adverse effects of PCV on perceived value among users of mobile shopping application is highlighted in the study; however, its role in safeguarding service quality is found to be insignificant.

A study with larger sample of respondents from varied nationalities will aid in generalizing the findings of this research.

This is the first time that PCV and its consequences have been studied in the context of mobile shopping applications.

Bicycle sharing offers a novel way to create smart and sustainable mobility solutions for the future. The purpose of this study is to draw on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) framework for identifying the factors necessary to predict bike-sharing intention among users in India.

Data were collected through a questionnaire distributed across four major cities in India, and 515 responses were analyzed. A sequential approach was employed to analyze the data using Partial Least Square–Structural Equation Modeling (PLS-SEM) and Fuzzy-set Qualitative Comparative Analysis (fsQCA).

The findings from PLS analysis revealed that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation and price value are the salient variables that affect users' intentions to participate in bike sharing. In addition, based on fsQCA, six configurations of causal conditions are presented as intermediate solutions that produce the same results. Although antecedent conditions, such as habit and social influence, had an insignificant effect on individuals' BSI, they create conditions sufficient to encourage users' participation in bike sharing in combination with other variables.

A few limitations of this research and the implications of the findings in terms of theory and policy implications are also discussed.

The reported study is one of the earliest to explain bike-sharing adoption in India using the UTAUT 2 model.

From the signaling theory perspective, the current study explores various drivers of brand transparency and its effect on users' interactions with food delivery apps.

First, a set of precursors of brand transparency of food delivery apps from focus group discussions was identified. Next, an integrated model tests the impact of brand transparency, perceived risk and brand trust on users' ordering frequency. Data collected from 522 users were analyzed using the partial least squares structural equation modeling method.

The outcomes showed the effectiveness of brand communications as the strongest indicator of brand transparency. Moreover, brand transparency favorably influences users' brand trust and ordering intention and negatively influences perceived risk. Hygiene rating attenuates the adverse effects of perceived risk.

The current study is a pioneering attempt that offers ways for online food delivery providers to build brand transparency, lessen users' risk perceptions and foster greater use of apps in the post-pandemic scenario.