Predicting changing pattern: building model for consumer decision making in digital market

The mediating role of exogenous shocks in green purchase intention: evidence from italian fashion industry in the Covid-19 era

This work investigates how the COVID-19 outbreak has affected consumers’ green purchasing intention in the fashion industry. It examines how this exogenous shock has influenced the relationship between consumer green purchasing intention and its three relevant antecedents (environmental knowledge (EK), environmental concern (EC), eco-friendly behaviour (EFB)). A survey of 1433 Italian consumers was carried out. The data were analysed through a structural equation modelling method to evaluate the direct and indirect mediating effects of the COVID-19 shock on the relationship between green purchasing intention and its antecedents (i.e., EK, EC and EFB) by considering traditional and online purchasing channels. The results of the model confirmed a positive relationship between green purchasing intention and its antecedents. The COVID-19 pandemic was also found to positively mediate the relationship between green purchase intention and two out of its three antecedents (i.e., EK and EC) in both traditional and online purchasing channels. This paper contributes to the literature on sustainable consumption by assessing magnitude of the relationship between green purchasing intention and its antecedents, and the mediating role exerted by a complex exogenous shock such as the COVID-19 outbreak.

Factors affecting Arab consumers' attitudes toward online shopping in light of COVID-19: the moderating role of digital marketing

Purpose

In both developed and developing countries, the COVID-19 pandemic has created a new generation of first-time online shoppers. More significantly, academics and practitioners believe that the shift to online shopping will continue in the years to come. Therefore, the purpose of this study was to examine the role of digital marketing tools as a moderator variable between the independent variables (i.e. consumption patterns, lifestyle, level of income, and payment methods) and dependent variable (i.e. the consumer's attitude towards online shopping) during the COVID-19 pandemic time in Arab countries.

Design/methodology/approach

A structured and self-administered online survey has targeted online shopping users in six different Arab countries based on a snowball and convenience sample. In total, 577 useable questionnaires were analyzed.

Findings

The findings show a significant positive relationship between the independent variables (i.e. consumption patterns, lifestyle, level of income, and payment methods) and the dependent variable (i.e. consumer attitude towards online shopping). Furthermore, the results reveal that the positive relationship between the independent and dependent variables is strengthened by the existence of the moderator variable, the digital marketing tools.

Research limitations/implications

This study was based on cross-sectional data collection, rather than a longitudinal study and collected data from six Arab countries. It is suggested that future research should expand the survey in more similar countries to broaden the database for further generalizations and use a longitudinal approach to better assess changes in attitudes over time. In addition, this study focused on the issue from a consumer's viewpoint, so it is recommended that future research could be conducted, but from the viewpoint of marketing managers.

Practical implications

This study represents a further deeper insight into consumer behaviour; it advocates giving more emphasis on organizations' awareness of their customers' consumption pattern, lifestyle, level of income, and payment method. The findings of this study can help managers and marketers to design a promotional mix to improve consumer's behaviour towards online shopping. The results suggest paying more attention to the high relevant effect of the consumption pattern, lifestyle, level of income, and payment method on the consumer attitude towards online shopping.

Originality/value

This paper is one of the few attempts that investigated consumer attitudes toward online shopping in the Arab world. Importantly, it identified the drivers of online shoppers' attitudes in the Arab world. This may be used to develop and implement e-marketing strategies. Furthermore, this paper examines the role of digital marketing as a moderator variable to provide empirical evidence to the body of knowledge of these drivers during the COVID-19 pandemic time in the Arab countries.

What Drives Consumer Purchasing Intention in Live Streaming E-Commerce?

The live streaming e-commerce market continues to grow with the rapid increase in contactless communication due to COVID-19. Live streaming e-commerce goes beyond the confines of traditional e-commerce of simply selling goods or services. It supplies information and allows synchronous information exchange between the online viewer (consumer) and the Internet celebrity, who influences the consumers information behavior and ultimately contributes to the long-term profit generation of the company. From online commerce to new retail and live streaming, China has been at the forefront of innovation in online commerce worldwide. Therefore, this study focuses on investigating the influences of live streaming e-commerce quality, such as service quality (SEQ), information quality (IQ), and system quality (SQ), on consumer purchase intention in China by applying the extended model of technology acceptance. Furthermore, this study analyzes the paths through which the live streaming e-commerce quality affects the consumer purchase intention, based on paths of perceived usefulness (PU), perceived ease of use (PEU), perceived trust (PT), and perceived value (PV). To analyze this study, the data were collected from 231 customers who had used live streaming e-commerce apps in China (e.g., TikTok, Taobao, and Jingdong) and empirical analysis was applied. The results were summarized as follows: SQ is positively related to PU and PT. Similarly, IQ is positively related to PEU and PT. In addition, SEQ is also positively related to PU and PEU. Moreover, SQ affected the PV through PU and PT significantly and ultimately influenced consumer PI. Also, the path in which SEQ affects PU, which in turn affects PV, and ultimately PI, was found. This study found out the paths of how the live streaming E-commerce quality affects the consumer purchasing intention and contributes to the research field of e-commerce and consumer behaviors. Additionally, the results of this study give useful marketing suggestions for relevant financial institutions and enterprises.

Advancing the Understanding of the Role of Responsible AI in the Continued Use of IoMT in Healthcare

This paper examines the continuous intention by healthcare professionals to use the Internet of Medical Things (IoMT) in combination with responsible artificial intelligence (AI). Using the theory of Diffusion of Innovation (DOI), a model was developed to determine the continuous intention to use IoMT taking into account the risks and complexity involved in using AI. Data was gathered from 276 healthcare professionals through a survey questionnaire across hospitals in Bahrain. Empirical outcomes reveal nine significant relationships amongst the constructs. The findings show that despite contradictions associated with AI, continuous intention to use behaviour can be predicted during the diffusion of IoMT. This study advances the understanding of the role of responsible AI in the continued use of IoMT in healthcare and extends DOI to address the diffusion of two innovations concurrently.

Differential effects of online signals on sales performance of local brand clothing products

Purpose

Businesses need to make quick decisions and adjustments to fulfill the growing online demand. Previous studies examined various factors affecting the online sales performance of products such as books, electronics and movies; however, they paid limited attention toward the local brand clothing products. The current study investigates the importance of different kinds of seller-generated and consumer-generated signals such as price, discount, product ratings, review volume, review sentiment, number of questions and interaction between some of these factors for predicting the sales performance of clothing products.

Design/methodology/approach

The multiple linear regressions has been employed to investigate the influence of various predictor variables on sales performance. The study also examines the importance of these predictor variables by using different machine learning models, including random forest (RF), neural networks and support vector regression (SVR).

Findings

The findings of the study emphasize the importance of price and discount rates offered on the product. The quantitative characteristics of reviews, such as review volume and average rating, have been found to be more important predictors than sentiment strengths. However, the sentiment strength of reviews with higher helpfulness scores plays a significant role in predicting sales performance.

Originality/value

The study highlights the varying importance of seller-based and consumer-based signals in predicting sales performance. It also investigates the interaction effect of these two kinds of signals. The consumer-generated signals have been further divided into two components based on social influence theory, and the interaction effects of these components have also been examined.

Purchasing Eco-Sustainable Products: Interrelationship between Environmental Knowledge, Environmental Concern, Green Attitude, and Perceived Behavior

Due to eco-sustainable marketing practices, customer consciousness has increased the use of eco-sustainable goods in India. This provides new opportunities for businesses and researchers in terms of eco-sustainable behavior; however, the market analysis in India is weak. This study examines the factors that trigger consumers to purchase eco-sustainable products and the interrelationship between environmental knowledge (EK), environmental concern (EC), green attitude (GA), and perceived behavior control (PB) among Indian consumers. The data were collected from 514 respondents, using purposive and snowball sampling. Using IBM SPSS 23.0 software, we employed exploratory factor analysis, a homogeneity test, Pearson’s correlation, and multiple regression for a multicollinearity test for data analysis. The results revealed that EK, EC, and GA are positively related and strongly influence eco-friendly purchasing behavior. Moreover, EK and EC are the strongest determinants of PB for eco-friendly products. This research will help green marketers to develop new green strategies to increase sales volumes and build relationships with target green customers.

Fulfilling External Stakeholders’ Demands—Enhancement Workplace Safety Using Fuzzy MCDM

Sustainable development and project stakeholder management indicate a business practice where an organization strives to fulfil the demands of the important stakeholders for the project’s success. If one company relies on subassembly parts from its supplier, then it might be considered that it has high interest for enhancing the business continuity of the supplier. This issue has become more complex during 2020 due to turbulent business conditions where the problem of the safety and health of workers during daily work has become one of main reasons for business vulnerability. Besides the above-mentioned, project stakeholders may have different demands. The implementation of the management actions that lead to the fulfilment of stakeholder demands (SDs), such as addressing ongoing issues, are almost always limited by the available budget. The contribution of this research is providing the input for determining the actions which should address the most important SDs. Those activities may be seen as part of the strategy for external stakeholder management and successful long-term relationship. The determination of the priorities of SDs is based on a fuzzy multicriteria optimization model with type-2 fuzzy sets.

Role of Online Retailers' Post-sale Services in Building Relationships and Developing Repurchases: A Comparison-Based Analysis Among Male and Female Customers

Customers are skeptical about shopping online because e-commerce environments are typically considered impersonal. To assure product quality and to enhance customer proclivity in such environments, post-sale services (i.e., product returns, exchange, and maintenance) may be considered to alleviate customers' skepticism. Therefore, this study's objective is to investigate the role of an online retailer's post-sale services (i.e., product return, exchange, and maintenance) on customers' attitudinal (building relationships) and behavioral aspects (developing customers' repurchase intentions). Structural equation modeling is applied to data collected through an online survey answered by 409 online customers of jd.com (after missing data were removed). Research findings show that product return, exchange, and maintenance services are strongly predictive of online customer satisfaction, and satisfaction significantly impacts customer trust. Both customer satisfaction and trust, as indicators of relationship quality, further mediate the links between product return, exchange, and maintenance services and online customer repurchase intention. In addition, differences between male and female customers were found in various aspects of online retailers' product return, exchange, and maintenance services. This is the first empirical study that not only examines the influence of all three dimensions of online retailers' post-sale services on customers' online shopping perceptions and decisions, but also considers differences between male and female customers. Finally, this research provides theoretical and managerial implications based on conceptual and empirical evidence.

Environmentally responsible freight transport service providers' assessment under data-driven information uncertainty

Purpose

Freight transportation practices accounted for a significant share of environmental degradation and climate change over the years. Therefore, environmentally responsible transport practices (ERTPs) become a serious concern of freight shippers and transport service providers. Past studies generally ignored the assessment of ERTPs of freight transport companies during a transport service contract. To bridge the above literature gap, this paper proposed a hierarchical framework for evaluating freight transport companies based on ERTPs.

Design/methodology/approach

In a data-driven decision-making environment, transport firm selection is affected by multiple expert inputs, lack of information availability, decision-making ambiguity and background of experts. The evaluation of such decisions requires a multi-criteria decision-making method under a group decision-making approach. This paper used a data-driven method based on the intuitionistic fuzzy-set-based analytic hierarchy process (IF-AHP) and VIseKriterijumska Kompromisno Rangiranje (IF-VIKOR) method. The applicability of the proposed framework is validated with the Indian freight transport industry.

Findings

The result analysis shows that environmental knowledge sharing among freight transport actors, quality of organizations human resource, collaborative green awareness training programs, promoting environmental awareness program for employees and compliance of government transport emission law and practice have been ranked top five ERTPs which significantly contribute to the environmental sustainability of freight transport industry. The proposed framework also ranked freight transport companies based on ERTPs.

Research limitations/implications

This research is expected to provide a reference to develop ERTPs in the emerging economies freight transport industry and contribute to the development of a sustainable freight transport system.

Originality/value

This study assesses the environmental responsibility of the freight transportation industry. The emerging economies logistics planners can use proposed framework for assessing the performance of freight transportation companies based on ERTPs.

A multi-attribute model to optimize the price and composition of prepaid mobile Internet plans

Purpose

Prepaid mobile Internet is one of the most profitable services that are composed of multiple attributes. The overall utility of Internet service can be broken down into the sum of the utility of individual attribute levels. Based on the multi-attribute theory, rational consumers choose the service that yields the highest utility from a number of possible alternatives. Determining the optimal attribute levels that satisfy consumers' preferences and maximize the total revenue of the firm is a challenging multi-attribute decision problem for any mobile operator. When designing mobile Internet services, adopting a robust composition of services against different realizations of competitors' strategies can bring advantages for network operators. The purpose of this study is to determine the optimal attribute levels of prepaid mobile Internet packages with the aim of maximizing the total revenue of the firm by considering the paradigms of multi-attribute utility theory about consumer choices and the issue of uncertainty in counterpart services offered by the competitors.

Design/methodology/approach

This paper formulates the problem of multi-attribute pricing and design of mobile Internet plans in a competitive environment by developing deterministic and robust scenario-based mathematical models and considering the paradigms of multi-attribute utility theory about consumer choices. The proposed robust scenario-based models are based on three different paradigms, including maximizing expected revenue, minimizing the negative deviation from expected revenue and minimizing the maximum regret. A comprehensive numerical analysis is conducted to evaluate and compare the efficiency of the proposed models.

Findings

The evaluations reveal that deploying recourse policy can result in higher revenue for the firm when facing uncertainty. By doing sensitivity analysis, this paper shows that consumer preferences for brand attribute and consumers' purchase frequency can influence the revenue of network operators.

Originality/value

This paper develops a novel deterministic multi-attribute product line design (PLD) model to address the problem of determining the price and composition of prepaid mobile Internet plans. Furthermore, the issue of uncertainty in counterpart services offered by the competitors is studied for the first time in the PLD literature.

Critical Components of Industry 5.0 Towards a Successful Adoption in the Field of Manufacturing

The fifth industrial revolution is known as Industry 5.0 and is being evolved to focus on the personalized demand of customers. This industrial revolution is required to provide better interaction among humans and machines to achieve effective and faster outcomes. It provides a new era of personalization and solves complex problems. Digital technologies provide a new paradigm in manufacturing and eliminate repetitive jobs. It applies human intelligence to understand the requirement of a human operator. The data in manufacturing can be analyzed using machine learning and artificial intelligence (AI). This paper discusses the development of all industrial revolutions and differentiates between Industry 4.0 and Industry 5.0. Further, it identifies the significant elements and capabilities of Industry 5.0 in the manufacturing field. This paper finally identifies 17 critical components of Industry 5.0 and discusses them briefly. Intelligent machines used in this revolution are efficiently used to solve real problems. It provides higher accuracy and speeds up the industrial automation with the help of critical thinking of human resources. Industry 5.0 provides computing power to the industry, which is to facilitate the digital manufacturing systems that are built to communicate with other systems. Thus, with mass personalization, there is customer delight with higher value addition through Industry 5.0.

Examining the impact of mobile interactivity on customer engagement in the context of mobile shopping

Purpose

This study aims to examine the impact of mobile interactivity dimensions (active control, personalization, ubiquitous connectivity, connectedness, responsiveness and synchronicity) on customer engagement.

Design/methodology/approach

A quantitative field survey study was conducted to collect the required data from actual users of mobile shopping in three countries: Jordan, the United Kingdom (UK) and Saudi Arabia.

Findings

The results are based on structural equation modelling and support the impact of five dimensions of mobile interactivity: active control, personalization, ubiquitous connectivity, responsiveness and synchronicity. The impact of connectedness is not supported. The results also support the significant impact of customer engagement on customer loyalty.

Research limitations/implications

This study only considered the shopping activities conducted by mobile channels, while other channels (e.g., online channels, traditional channels and social media shopping channels) are not considered. Furthermore, the current model does not consider the impact of personal factors (e.g., technology readiness, self-efficacy and user experience). The results of the current study present a foundation that can guide marketers and practitioners in the area of mobile shopping.

Originality/value

This study enriches the current understanding of the impact of mobile interactivity on mobile shopping, as well as how mobile interactivity can enhance the level of customer engagement.

Blockchain in logistics industry: in fizz customer trust or not

Purpose

The study is an attempt to explore much talked but less understood issue of “blockchain in logistics industry” in modern perspective. The customers' acceptance of blockchain technology in logistics and supply chain is tested through “Technology Acceptance Model” by using attitude, perceived usefulness (PU), perceived ease of use (PEOU), behavioral intention and use behavior.

Design/methodology/approach

Data has been collected through online and offline medium, where active 240 responses have been collected finally using convenience sampling. Confirmatory factor analysis with structural equation modeling (SEM) was carried out for data analysis.

Findings

The customers' acceptance of blockchain technology in logistics and supply chain is tested through “Technology Acceptance Model.” The findings reveal model fit where PEOU, PU and attitude are the major constructs of the model to realize the substantial gains in logistics process efficiency.

Research limitations/implications

Convenience sampling has been considered for the study to collect the data of online users of various technology applications for tracking and shipment detail, whereas a more specified method sampling can be considered for the future research. The study has been conducted in the Indian context, which has been considered as the limitation pertaining to generalization across countries and industries.

Practical implications

The findings of this study will be helpful for market practitioners to build transparency between customers and industry to overcome the frictions in logistics. Blockchain will help in monitoring the performance history and previous commitments of logistics professionals resulting in selecting a responsible logistics solution provider. Access to critical data by the authorized member of the supply chain will reduce unsubstantiated disputes.

Social implications

Blockchain technology will be available to everyone on the network. This will bring transparency and help logistics professionals such as carriers, shippers and brokers to detect early frauds and prevent thefts. It will increase customer trust toward any financial transaction for tracking the ownership of titles.

Originality/value

Blockchain technology is envisioned to be a technology that could be a game-changer for decentralizing infrastructure, introducing transparency and building trust in the supply chain. The current study is a novel addition to the literature where blockchain technology enables the indisputable storage of verified data that was previously kept in safeguarded silos.

Economic consequences of consumer repair strategies for electrical household devices

Purpose

The purpose of this paper is to investigate to what extent a consumer’s repair strategy impacts the annual costs of ownership of a washing machine and two types of vacuum cleaner.

Design/methodology/approach

The annual cost of ownership is determined by calculating the annual life cycle cost (LCC) for the respective devices. The annual LCCs of the different scenarios allow a comparison of the different repair strategy options. A Monte Carlo simulation is run to introduce parameter variability. The device’s failure rate is estimated by a combination of data sets on the devices’ performance.

Findings

Results demonstrate that the repair of the devices considered is a more favourable option over replacement. A consumer who aims for the lowest annual LCC should allow for a high number of repairs per device, without putting a maximum on the cost per repair. However, the consumer should become more cautious when a device approaches the end of its expected lifetime. Finally, the purchase of warranty can be interesting when the warranty covers a sufficiently long proportion of the device’s (expected) lifetime and when its cost does not exceed a threshold proportion of the initial purchase price.

Research limitations/implications

The costs for repair might be overestimated. Future research can focus on the reduction of repair costs following self-repair.

Practical implications

The results provide strong arguments in favour of repair instead of replacement of broken devices.

Originality/value

This is the first research to quantify the influence of consumer behaviour in the context of repair of devices on the ownership costs of these devices.

A cross-cultural analysis of perceived product quality, perceived risk and purchase intention in e-commerce platforms

Purpose

While there have always been cultural differences between countries and between individuals, the virtualisation of markets is rendering the impact of these differences even more salient. There is clear evidence that cultural dimensions are relevant in the adoption and use of e-commerce. The purpose of this paper is to analyse the significant effects of individual cultural dimensions on perceived product quality, perceived risk and purchase intention in e-commerce platforms.

Design/methodology/approach

A questionnaire was developed to serve as a tool of measurement. A confirmatory factor analysis was conducted to examine whether all the indicators for the constructs are reliable. A multiple regression analysis was carried out to test the hypotheses.

Findings

The results reveal that, in the case of e-commerce platforms, the cultural dimensions uncertainty-avoidance and collectivism exert a significant influence on perceived product quality, perceived risk and purchase intention.

Research limitations/implications

The present study is based on real well-known e-commerce platforms which could have influenced the responses of the sample due to potential past experiences of use. An experimental design based on fictitious platforms could offer more objective findings.

Practical implications

This research contributes to the understanding of e-commerce and the behaviour of consumers during online purchasing, taking into account the cultural differences that may exist between them.

Originality/value

The literature on individual cultural dimensions – that is, non-national cases – and the variables analysed in the present study suffers from great limitations. This study complements a growing interest in analysing the individual cultural dimensions and their effects on the sphere of e-commerce, specifically on perceived product quality, purchase intention and perceived risk during browsing, measured in terms of the six types of risk prevalent in e-commerce platforms.