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The study aims to explore the role of reliance and brand image (goods-based and service-based) in risk perceptions related to business-to-business (B2B) purchases. In particular, time risk (TR), performance risk (PR) and financial risk (FR) has been explored in this paper.

A questionnaire-based survey data has been collected from 152 respondents from different industries, and the model was validated using partial least squares structural equation modeling.

The study highlights the importance of reliance and brand image for reducing the effects of perceived risk. While reliance is negatively related to all the risk dimensions, the relationship between reliance and FR is serially mediated by service-based brand image (SBBI) and TR. The same is also mediated by PR. Furthermore, PR and TR are positively related to FR.

The findings of this study highlight the importance of reliance and brand image for reducing the effects of risk dimensions. Reliance plays an important role in reducing all risk perceptions. Findings also highlight the importance of SBBI in reducing TR.

The findings provide managers with key insights for reducing risk perceptions by creating a strong reliance and B2B brand image, leading to long-term relationship strategies.

To the best of the authors’ knowledge, this is one of the few papers in B2B marketing that focuses on the importance of reliance and brand image in reducing the effects of perceived risk.

The purpose of this study is to explore the impact of other customer's opinion on a service firm and its alliance on the evaluation of the airline by the focal customer by integrating qualitative and quantitative user-generated content. The study also explores the relative importance of core and peripheral attributes in consumer evaluations.

A text mining and natural language processing-based approach was followed to extract insights from the qualitative part of 18,457 consumer reviews, which were later analyzed along with the quantitative information obtained from the reviews using linear regression and logistic regression methods.

The authors found that customer satisfaction and recommendation behavior is formed by own and others' opinion about the airline and alliance. The relative importance of the core and peripheral attributes depends on the psychological distance from the evaluation of the attribute.

The theoretical contribution and managerial implications have been discussed in detail.

It helps in review management strategy, service design strategy and the alliance and partnership strategies of the airlines.

This is the first paper that explores the impact attribute-level evaluations found in prior reviews on the future reviews of customers. It also explores the effect of prior reviews in the context of a service business and its alliances.

This study aims to explore the antecedents and consequences of reliance and its relationship with trust in the context of business-to-business (B2B) branding. The study also explores the above relationships in various B2B contexts.

Survey data of 135 respondents from different B2B firms was analyzed, and the proposed theoretical model was validated using partial least square structural equation modeling technique followed by multigroup analysis.

The results suggest that commitment, management capability and innovation capability are positively related with reliance, while trust acts as mediator between commitment–reliance relationships. Moreover, while both reliance and trust lead to B2B brand image, reliance has higher relationship strength. Furthermore, reliance mediates the trust–brand image relationship too.

The paper contributes to the literature of reliance and its role in B2B brand image by providing newer insights about the antecedents and consequences of reliance and its relationship with trust.

The findings provide managers with key insights for creating B2B brand image using reliance and trust by focusing on capabilities and commitment.

To the best of the authors’ knowledge, this is one of the few papers in B2B marketing which focuses on the antecedents of reliance and relative importance of trust and reliance.

The purpose of the study is to develop a structural and a predictive model of the future purchase behavior of the consumers from value, quality and satisfaction and also finding the role of consumer loyalty in the above-mentioned model.

Based on survey and purchase data of a sample of 235 respondents, the authors have used structural equation modeling to develop a structural model and three-stage least square regression to develop and validate the predictive model.

In the structural model, the authors found that perceived service quality and network quality leads to customer satisfaction which also leads to loyalty intentions. However, neither past purchase behavior nor loyalty has significant predictive power to predict future usage. But the interaction effect of loyalty and past purchase predicts future purchase significantly.

The study went beyond structural model and developed a behavioral predictive model which can overcome self-reporting bias. Also, the study focused on the moderating role of loyalty in predicting future purchase quantity, thus contributing toward the theoretical understanding of the effects of loyalty.

Other than providing a forecasting model, the study helps the service managers to understand the importance of the relational constructs than the tangible constructs. Moreover, it also suggests optimally target the big buyers through the loyalty programs to ensure higher future revenues.

The study provides new insight on the impact of loyalty intention of consumer’s purchase behavior and shows the boundary conditions of predictive power of loyalty intention and past purchase on future purchase. Moreover, this is one of the very few studies that have focused on these relationships in Indian context.

This study aims to identify evolution and advancement in the field of business-to-business (B2B) loyalty knowledge area by analyzing its intellectual structure.

The authors use bibliometric analysis for quantitative evaluation of scholarly studies published on B2B loyalty area over a period of 27 years (1993–2020). The authors analyze intellectual knowledge base of B2B loyalty area by looking into 263 studies with 14,028 references authored by 693 researchers.

The results provide a comprehensive review of B2B loyalty area by identifying its foundations, influential works and intellectual communication linkage between these works. Notably, the analysis reveals most cited studies, key authors, important keywords, intellectual turning points and emerging trends of research in the discipline.

This study creates a baseline for presenting precise and comprehensive insights into research themes in B2B loyalty area, and identifies progressive trends over a period. This study is also helpful for researchers in identifying future directions of research in the discipline.

This study reveals the intellectual structure of B2B loyalty area.

Though extant literature has identified goods-based brand image (GBBI) and services-based brand image (SBBI) as drivers of business-to-business (B2B) loyalty, their relative importance has remained unexplored. This study aims to bridge this gap.

The authors have used a retrospective sampling-based methodology to collect data from B2B customers via an offline survey with a sample size of 125 purchase managers.

The authors found that both GBBI and SBBI have positive relationships with B2B loyalty, with customer satisfaction being the mediator. Using the construal level theory (CLT), the authors argue that the B2B purchase term, vendor–customer relationship strength and physical accessibility of the vendor are associated with the construal level of the purchase context. Further, the authors show that B2B customers give higher importance to GBBI in lower construal level and higher importance to SBBI in higher construal level. The authors have also found the moderated mediation effect of customer satisfaction in GBBI–loyalty and SBBI–loyalty relationships with construal level as moderator.

This study contributes to extant literature of B2B branding and purchase decision-making by bringing in concepts of CLT. It also extends the literature of the GBBI–SBBI–loyalty relationship by bringing in newer results, which reassure the coexistence of goods-dominant and service-dominant logic in the B2B marketplace.

Important managerial implications have been discussed to help B2B managers in brand building, product–service design and relationship management.

This paper is a pioneer in using the CLT in the B2B purchase contexts. It also provides a theoretical and psychological underpinning of goods–service dilemmas in the B2B context, which is also noble.

Extant literature on queuing has identified service queues as social systems where social justice is an important factor for service evaluation. First-order justice, defined as a first-come first-served (FCFS) process, has been found to be a necessary condition of social justice and positive evaluation. Second-order justice, defined as equal waiting time, has been found to be an additional factor which comes into play only when first-order justice is met. This paper aims to show that in the emerging market situation, the above definitions of justice and the order mentioned above does not work.

Instead of equal wait, the study has focused on equitable wait, i.e. waiting duration is in sync with the service needs. Three experiments have been performed to establish the hypotheses suggested.

FCFS is found not to be the necessary condition as it was in the extant literature and can be relaxed sometimes to get higher service evaluation by ensuring justice from the equitable wait. The study also portrays the interaction effects of the two types of social justice on service evaluation. Moreover, the impact of justice from equitable wait on service evaluations is found to be moderated by perceived personal connect of the service provider and the consumer, perceived importance of system and process and perceived ability of the service provider of capacity improvement and mediated by perceived control of service provider on providing the justice of equitable wait.

The study contributes toward the understanding of social justice in service queues. It also contributes to the literature of attribution theory and consumer betrayal.

The study provides suggestions to retail managers in emerging markets to choose queue management strategies depending on the size of the retail shops and consumers’ expectations from them.

The study introduces the concept of justice from the equitable wait, which is original in the queuing literature to the best of the author’s knowledge. The study also finds a new order of justice in the emerging market scenario.

The purpose of this research is to propose and validate a theoretical framework explaining web-rooming and showrooming as a multi-stage decision-making process. The authors have used consumer purchase decision-making theories to propose a model that identifies showrooming and webrooming as a combination of two decisions, channel choice during information search and channel choice during actual purchase. Further, the authors explored how various antecedents of showrooming and webrooming have differential effects on various stages of a purchase decision-making process and how product type moderates the relationships.

The authors have conducted empirical research, whereby 243 responses were obtained from a cross-sectional survey. The authors have used structural equation modeling and multiple regression analysis to validate our theoretical model.

Webrooming or showrooming is a multi-stage decision-making process for the consumers. First, consumers decide whether to search online or offline and then whether to buy online and offline. Different individual, purchase context-related and channel related factors impact these decisions. Product type governs which variables will be more important than others.

The research looks to enhance the understanding of the consumer's decision-making process during showrooming and webrooming while also helping retailers design and implement appropriate strategies that could affect consumers during information search and actual purchase.

The extant literature has utilized the SERVQUAL scale to measure service quality dimensions and their importance towards customer-satisfaction using close-ended survey-based questions and not open-ended questions and/or user-generated qualitative responses. On the other hand, while measuring customer-satisfaction drivers from user-generated content (UGC), extant studies have majorly used overall or aspect-wise evaluations and not evaluations specific to SERVQUAL dimensions. In this study, the authors try to bridge the gap.

The authors suggest a methodology consisting of text mining, machine learning and econometric techniques that can measure consumer evaluations of SERVQUAL dimensions. The authors used qualitative and quantitative UGC obtained from 27,052 online reviews on 362 airlines by reviewers of 158 nationalities for our analysis.

The authors established a unique method which combines qualitative and qualitative UGC to measure service quality. The authors have also uncovered the comparative importance of such dimensions in creating customer-satisfaction and recommendation in the context of the airline industry.

The paper is one of the pioneering studies that try to find measures of SERVQUAL dimensions from online consumer reviews and their influence on customer satisfaction.

In the age of social media, when publishers are vying for consumer attention, click-baits have become very common. Not only viral websites but also mainstream publishers, such as news channels, use click-baits for generating traffic. Therefore, click-bait detection and prediction of click-bait virality have become important challenges for social media platforms to keep the platform click-bait free and give a better user experience. The purpose of this study is to try exploring how the contents of the social media posts and the article can be used to explain and predict social media posts and the virality of a click-bait.

This study has used 17,745 tweets from Twitter with 4,370 click-baits from top 27 publishers and applied econometric along with machine learning methods to explain and predict click-baitiness and click-bait virality.

This study finds that language formality, readability, sentiment scores and proper noun usage of social media posts and various parts of the target article plays differential and important roles in click-baitiness and click-bait virality.

The paper contributes toward the literature of dark behavior in social media at large and click-bait prediction and explanation in particular. It focuses on the differential roles of the social media post, the article shared and the source in explaining click-baitiness and click-bait virality via psycho-linguistic framework. The paper also provides explanability to the econometric and machine learning predictive models, thus performing methodological contribution too.

The paper helps social media managers create a mechanism to detect click-baits and also predict which ones of them can become viral so that corrective measures can be taken.

To the best of the authors’ knowledge, this is one of the first papers which focus on both explaining and predicting click-baitiness and click-bait virality.