Omnichannel Retailing in Light of Psychological Factors: A Mediated Model

Purpose

Retail businesses have been seeing dramatic changes in the last decades. It has evolved from single-channel retailing to omnichannel retailing, providing a seamless shopping experience to customers. Customers armed with modern technology are creating challenges for retailers and forcing them to create an omnichannel environment. So, implementing an omnichannel retailing strategy is a big challenge for retail managers in the age of modern technologies. Retailers could evaluate consumers' usage intention of omnichannel retailing based on technological and psychological factors. However, research based on psychological factors is limited in the prevailing literature on omnichannel retailing. Based on the Motivational Model (MM) and Big-Five Factors (BFF) of personality traits, the study tried to fill the gap regarding the influence of psychological factors on omnichannel usage intention.

Methods

A sample of 724 respondents through a structured questionnaire from a developing economy. The target population of the current study was internet users, as they might be prospective Omni shoppers in the near future. Relationships were tested through Structural Equation Modeling (SEM) with AMOS 23.

Results

Results revealed that personality traits directly correlate with omnichannel usage intention, while motivations (intrinsic and extrinsic) partially mediate these relationships. Moreover, the results of the current study also revealed that the personality traits extraversion, agreeableness, and conscientiousness are vital antecedents of behavioral intention. Intrinsic and extrinsic motivations positively impact consumers' usage intention, while extrinsic motivation partially mediates intrinsic motivation and consumers' usage intention. Additionally, full mediation prevails in the association of consumers' usage intention and personality traits (emotional stability and Openness to experiences).

Originality

The domino effects provide a solid theoretical milestone in understanding the phenomenon of omnichannel retailing strategy and facilitates marketing managers to design channel strategies for emerging economics.

Understanding the factors affecting AI services adoption in hospitality: The role of behavioral reasons and emotional intelligence

This study explores the reasons (for and against) the adoption of AI in the hospitality industry among Pakistani customers. The hypothesis was tested using the sample obtained from Pakistani hospitality customers. The data is collected via an online survey and analyzed with the structural equation modeling and PROCESS macro. The study results indicate that cultural values positively associate reasons for, attitudes, and intentions to adopt. Moreover, the results prove that attitude mediates the relationship between reasons (for and against) and intention to adopt AI services in hospitality. Furthermore, the finding shows that customer emotional intelligence has no moderation effect on attitude and intention to adopt AI services. This study highlights technological complexity and safety concerns are the most significant barriers in the studied context. Further, addressing reason against (technological complexity and safety concerns) may allow policymakers to lessen the present customer attitude-intention gap by tackling the factors that cause customers to resist adopting AI services in hospitality. In this respect, marketers should develop a marketing campaign strategy focusing on the benefits of the adoption of AI services in comparison to employee service. This is the first empirical study examining cultural values, reasons (for and against) attitudes, their relationship with intentions, and moderating role of an attractive, important, yet ignored variable, customer emotional intelligence. This study confirms that the behavioral reasoning theory can better describe the customers' adoption behavior of AI services in the hospitality sector.

Predicting Bitcoin (BTC) Price in the Context of Economic Theories: A Machine Learning Approach

Bitcoin (BTC)-the first cryptocurrency-is a decentralized network used to make private, anonymous, peer-to-peer transactions worldwide, yet there are numerous issues in its pricing due to its arbitrary nature, thus limiting its use due to skepticism among businesses and households. However, there is a vast scope of machine learning approaches to predict future prices precisely. One of the major problems with previous research on BTC price predictions is that they are primarily empirical research lacking sufficient analytical support to back up the claims. Therefore, this study aims to solve the BTC price prediction problem in the context of both macroeconomic and microeconomic theories by applying new machine learning methods. Previous work, however, shows mixed evidence of the superiority of machine learning over statistical analysis and vice versa, so more research is needed. This paper applies comparative approaches, including ordinary least squares (OLS), Ensemble learning, support vector regression (SVR), and multilayer perceptron (MLP), to investigate whether the macroeconomic, microeconomic, technical, and blockchain indicators based on economic theories predict the BTC price or not. The findings point out that some technical indicators are significant short-run BTC price predictors, thus confirming the validity of technical analysis. Moreover, macroeconomic and blockchain indicators are found to be significant long-term predictors, implying that supply, demand, and cost-based pricing theories are the underlying theories of BTC price prediction. Likewise, SVR is found to be superior to other machine learning and traditional models. This research's innovation is looking at BTC price prediction through theoretical aspects. The overall findings show that SVR is superior to other machine learning models and traditional models. This paper has several contributions. It can contribute to international finance to be used as a reference for setting asset pricing and improved investment decision-making. It also contributes to the economics of BTC price prediction by introducing its theoretical background. Moreover, as the authors still doubt whether machine learning can beat the traditional methods in BTC price prediction, this research contributes to machine learning configuration and helping developers use it as a benchmark.

Role of social media marketing activities in China’s e-commerce industry: A stimulus organism response theory context

Social media marketing has become one of the most significant growth paths for many businesses in today’s world. However, many companies are still unclear about using social media marketing to get their advantages, particularly in an e-commerce environment. In this background, this study is proposed to examine the effects of social media marketing activities (SMMAs) (interactivity, informativeness, word-of-mouth-WOM, personalization, and trendiness) on relationship quality, such as commitment, trust, and satisfaction in order to predict consumers’ online repurchase intentions in China’s e-commerce environment. This study proposed a theoretical model by using the stimulus-organism-response (S-O-R) theory. Using a structured questionnaire and purposive sampling, this study examined the responses of 403 consumers through partial least square-structural equation modeling. The findings discovered that SMMAs significantly strengthen the relationship quality factors, such as commitment, trust, and satisfaction, which in turn positively increase consumer online repurchase intentions in China’s e-commerce industry. This is novel research that contributes to the S-O-R theory and provides several managerial guidelines that assist managers in improving their business performance in the e-commerce industry. This research also highlighted some limitations.

Firm innovation activities and consumer brand loyalty: A path to business sustainability in Asia

Background

In recent years, technological advancements have increased the importance of innovation activities. Therefore, firms invest millions of dollars in innovation activities to ensure long-term business sustainability. Similarly, consumer concerns have increased dramatically over the past years. Thus, brand loyalty has become a top priority for firms and consumers. In this background, this research examines how firms' innovation activities translate into consumer brand loyalty to assure business sustainability in Asian markets, particularly China, Pakistan, and Indonesia.

Objectives

This study's specific objectives are to comprehend the concept of firms' innovation activities and their effect on the brand prototype. Examine the effect of the brand prototype on global brand preference, recommendation, and loyalty among Asian consumers. Find out the impact of brand preference on brand recommendations and the influence of brand recommendations on brand loyalty among Asian consumers.

Materials and methods

A total of 814 consumers from Asian countries (China, Pakistan, and Indonesia) participated in this study, and structural equation modeling was used to analyze the data.

Results

The findings indicate that firms' innovation activities, such as processes, products, and store environment, positively influenced the brand prototype, thereby increasing consumer brand knowledge. Likewise, brand prototype contributes to developing brand preference, brand recommendation, and brand loyalty among Asian consumers. Lastly, consumer brand preference significantly influenced brand recommendation, which positively improves consumer brand loyalty in Asia.

Conclusion

This study concluded that Asian (Chinese, Pakistani, and Indonesian) consumers have favorable perceptions of firms' innovation activities (i.e., process, product, and store environment innovation), which influences their ability to develop brand prototypes to increase consumer brand knowledge. Similarly, brand prototype fosters brand preference, recommendation, and loyalty. Likewise, favorable brand preference encourages consumers to recommend the brand to others, strengthening brand loyalty. Thus, firms should invest in innovation activities to strengthen consumer brand loyalty in Asian markets. Consequently, this study may assist multinational corporations in increasing their business volumes and market shares in Asia.

Managerial recommendations

This study provides important managerial recommendations. The findings revealed that global managers can develop and implement several branding strategies for sustaining their businesses in the Asian environment.

Consumer Perceptions of Brand Localness and Globalness in Emerging Markets: A Cross-Cultural Context

The globalization of markets and consumer behavior has changed dramatically in recent years. Similarly, global and local brands are facing many challenges in emerging markets. Thus, in this backdrop, this research is intended to examine the impact of consumer perceptions of brand localness and globalness on brand attitude in order to predict consumer behavioral intentions (purchase intention, price premium, and word of mouth) in cross-cultural emerging markets (China and Pakistan). Additionally, this research considered the moderating effects of consumer ethnocentrism and brand familiarity as a control variable. This study used an online survey to examine 1,562 responses from Chinese (n = 768) and Pakistani (n = 794) consumers regarding local and global brands. The proposed hypotheses were analyzed by using the partial least square-structural equation modeling method. The findings indicated that the consumer perceptions of brand localness and brand globalness had a substantial impact on brand attitude, which in turn favorably influenced consumer behavioral intentions in China and Pakistan. The brand attitude was a crucial mediator in both markets but was more critical in China than Pakistan. The interaction moderating effects of consumer ethnocentrism and consumer perceptions of brand localness positively influenced brand attitude in China, whereas consumer ethnocentrism and consumer perceptions of brand globalness negatively influenced brand attitude in Pakistan. Interestingly, brand familiarity was discovered a substantial control variable in both markets, except for purchase intention in Pakistan. This research contributed to Fishbein’s attitude theory and social identity theory. This research offers important recommendations to local and global marketers and brand managers in formulating and employing several positioning, market segmentation, and targeting strategies that may assist them in competing effectively in emerging markets.

Impact of Performance Lower Than Expectations on Work Behaviors: The Moderating Effect of Status Mutability and Mediating Role of Regulatory Focus

Purpose

Drawing on social cognitive theory (SCT), this research aims to test the mediation of promotion focus motivation in between performance lower than expectations and innovative work behavior under the moderation of status hierarchy mutability. Further, low performance may also lead employees to counter-productivity through prevention focus. Thus, this study examines both sides of performance lower than expectations of the employee in the organization.

Methodology

The study considered a cross-sectional study and surveyed R&D departments of manufacturing firms located in China. In total, 340 employees in 65 teams participated in the survey. This study conducted a confirmatory factor analysis to test the reliability and validity of data and used hierarchical linear modeling to test the hypotheses via Mplus 7.3.

Findings

First, we reveal that employees’  performance lower than expectations is positively linked with promotion focus regulation. Second, the study’s outcomes reveal a positive indirect effect from employees’ higher status mutability in the group toward innovative work behaviour through promotion focus motivation. At last, the study identified that performance lower than expectations has a positive indirect impact on counterproductive behaviour via prevention focus.

Practical Implications

This research assists managers to understand the connection of stress between performances lower than expectations and the self-regulated motivation of the employee towards innovative behavior and counterproductive work behavior. Further, it recommends that leaders at different levels should understand that various reference groups inside and outside the organization pressurize employees’ cognition. Therefore, certain steps and policies (eg, sensitive training, annual performance appraisal, feedback) must be taken into consideration to handle such self-regulatory behaviors.

Originality

This study is the earliest to examine the performance expectations as an antecedent of innovative work behavior and counterproductive work behavior through regulatory focus.