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The purpose of this study is to understand customer experience (CX) in business-to-business (B2B) markets through the perspectives of buyer–seller dyads. This study aims to evaluate how customer journey, touchpoints and digital and social media (DSM) influence CX and offer avenues for sellers to align their efforts with buyers’ requirements to create and manage CX.

Integrating insights of practicing buyers and sellers in the pharmaceutical B2B industry, this study follows the phenomenological approach to understand their experience through their perspectives on the customer journey, touchpoints and DSM.

The findings of this study include convergence in the perspectives in journey stages, journey enablers, stakeholder involvement, touchpoint preference and DSM’s use. The study findings also include divergence in perspectives in the senior management engagement, journey enablers, selling center involvement, DSM purpose and usage of DSM platforms. These offer opportunities for sellers to align with buyer journey, touchpoints and DSM to create and manage CX.

Sellers in pharmaceutical B2B markets have been dependent on traditional knowledge to influence customer journey and touchpoints and the advent of DSM has enhanced the challenge. To avoid this confusion, sellers need to have clarity of customers’ expectations on the journey, touchpoints and DSM. This enables sellers to allocate their resources better to achieve the desired outcome in CX.

This first-of-its-kind study captured the convergence and divergence perspectives of pharmaceutical B2B buyer–seller dyads from the lens of the uncertainty reduction theory and social penetration theory. The study suggests opportunities for pharmaceutical sellers to create and manage CX.

Grounded in strategic fit theory, this study aims to identify external and internal factors that influence retailers’ strategic choices regarding their own product brands. Furthermore, it seeks to explore the variations between different own product brand strategies in achieving both external and internal strategic fit.

The systematic review method, incorporating a thematic analysis, was adopted, and 318 articles were included for review.

The factors that influence retailers’ strategic choices regarding their own product brands encompass a range of external macro and industrial environmental factors, along with various internal resource and capability factors. Moreover, the effects of these factors vary across different own product brand strategies.

To our knowledge, this is the first systematic review of research on retailers’ own product brands from a strategic management perspective, offering systematic and structured guidance for retailers.

The public sector (PS) has extensively utilized information technology (IT); however, research reveals that the failure rate remains high, particularly for national and sectoral IT (NaSIT) applications. To this end, numerous studies have been conducted to gauge the success of IT applications, where a significant number have demonstrated the importance of planning in this regard. Consequently, the current study aims to investigate the factors that influence the success of NaSIT planning and implementation within this sector.

A qualitative methodology and a systematic literature review encompassing papers indexed in seven databases until November 2022 were utilized.

The review of 92 selected papers revealed that the success of NaSIT planning and implementation is influenced by a number of factors divided into nine main categories. These include vision, goals and objectives; alignment; interoperability; infrastructure; involvement; equity and digital divide; privacy, security and trust; administration; and culture. Human, social, economic and organizational factors comprise the vast majority of these factors. By addressing these factors, the failure rate of IT plans can be reduced. Governments will be able to effectively employ this technology to accomplish their missions if these factors are considered in order to decrease the failure rate of IT plans.

By examining the factors that influence the success of NaSIT planning and implementation in the PS, this study attempts to provide a comprehensive view of various types of research. Furthermore, policymakers can employ this perspective to improve the efficiency and effectiveness of the PS.

It is crucial for the Indian micro, small and medium enterprises (MSMEs) to implement a few of the most important Industry 4.0 (I4.0) technologies and reap maximum benefits of sustainability. This paper aims to prioritize I4.0 technologies that can help achieve the sustainable operations and sustainable industrial marketing performance of Indian manufacturing MSMEs.

I4.0-based sustainability model was developed. The model was analyzed using data collected from MSMEs by deploying analytic hierarchy process and utility-function-based goal programming. To have a better understanding, interviews were conducted.

Predictive analytics, machine learning and real-time computing were found to be the most important I4.0 technologies for sustainable performance. Sensitivity analysis further confirmed the robustness of the results. Business-to-business sustainable marketing is prioritized as per the sustainability need of operations of industrial MSME buyers.

This study uniquely integrates literature and practitioners’ insights to explore I4.0’s role in MSMEs sustainability in emerging economies. It fills a research gap by aligning sustainability goals of industrial buyers with suppliers’ marketing strategies. Additionally, it offers practical recommendations for implementing technologies in MSMEs, contributing to both academia and industry practices.

This study investigates the influence of e-marketing risks on a Corporation’s Reputation (CR) resulting from its online marketing of products and services.

A comprehensive analysis was conducted to enhance the company’s e-marketing strategies and bolster its reputation in the market. This involved an investigation into key factors of e-marketing risks, such as customer confidence, product quality, marketing fraud, credibility and customer knowledge and proficiency in using online platforms. These factors have directly impacted the company’s reputation, including aspects such as product/service quality, attractiveness, performance and commitment to social responsibility.

Its finding indicates that customers' lack of confidence in e-marketing has a strong impact on CR, followed by product quality and credibility. The absence of consumer awareness about e-marketing websites and e-fraud frequently negatively affects the organizational reputation.

To enhance the corporation’s reputation, it is recommended that companies provide educational resources on online shopping, including guidance on using the company’s website, comparing prices and other services that facilitate online purchases. This will help to support the credibility of e-marketing and enhance customer trust.

This research is an exploration of how e-marketing has affected a Corporation’s Reputation. It provides modern knowledge about the dynamic interplay between digital strategies and brand perception. Investigating this relationship provides valuable insights into the evolving landscape of consumer trust in the digital age. By analysing the various ways in which e-marketing influences a company’s reputation, innovative approaches can be developed to enhance its online presence and build lasting customer trust.

Machine learning (ML) techniques are increasingly important in enabling business-to-business (B2B) companies to offer personalized services to business customers. On the other hand, humans play a critical role in dealing with uncertain situations and the relationship-building aspects of a B2B business. Most existing studies advocating human-ML augmentation simply posit the concept without providing a detailed view of augmentation. Therefore, the purpose of this paper is to investigate how human involvement can practically augment ML capabilities to develop a personalized information system (PIS) for business customers.

The authors developed a research framework to create an integrated human-ML PIS for business customers. The PIS was then implemented in the energy sector. Next, the accuracy of the PIS was evaluated using customer feedback. To this end, precision, recall and F1 evaluation metrics were used.

The computed figures of precision, recall and F1 (respectively, 0.73, 0.72 and 0.72) were all above 0.5; thus, the accuracy of the model was confirmed. Finally, the study presents the research model that illustrates how human involvement can augment ML capabilities in different stages of creating the PIS including the business/market understanding, data understanding, data collection and preparation, model creation and deployment and model evaluation phases.

This paper offers novel insight into the less-known phenomenon of human-ML augmentation for marketing purposes. Furthermore, the study contributes to the B2B personalization literature by elaborating on how human experts can augment ML computing power to create a PIS for business customers.

This study aims to explore the role customer satisfaction play in mediating the nexus between commitment, trust, relative dependence and customer loyalty from an emerging market context under a business-to-business (B2B) setting.

The study was a descriptive survey, and using convenience sampling technique, questionnaires were used to gather data from 356 businesses that were distributors of Guinness Ghana Company Limited. Partial least squares structural equation modeling was used to test the proposed hypotheses for this study, and macro-PROCESS was performed to test the mediating effect of customer satisfaction.

The findings show that relative dependence had the most considerable significant and positive impact on B2B partners satisfaction, followed by commitment and trust, respectively. A positive and significant relationship was also found between B2B firms’ satisfaction and loyalty. The result also indicates that customer satisfaction mediates the relationship between commitment, trust, relative dependence and B2B loyalty.

Practitioners can manipulate specific relative dependence, commitment and trust features to increase customer satisfaction with their firm’s services, thus ensuring longer-term customer loyalty.

Drawing on the social exchange theory, this study provides a more profound perspective focusing on an emerging market context, by examining from a B2B setting the significance of commitment, trust, relative dependence and B2B partners satisfaction on loyalty.

The research aims to qualitatively explore e-marketplace service quality (EMSQ) from the perspective of an industrial buyer as a sole decision-maker. It further intends to quantitatively examine its impact on the industrial buyer's perceived value (PV), overall satisfaction (SAT), and e-loyalty (ELOY) in the context of business-to-government (B2G) e-commerce.

The research used an exploratory sequential mixed-method design. A qualitative exploratory study of EMSQ was conducted using a Straussian grounded theory (GT) technique, followed by an explanatory quantitative study using PLS-SEM to evaluate causal links between various research variables.

In the area of e-services, the investigation found that the hierarchical structure of EMSQ encompasses six broadly applicable dimensions and one B2G context-specific dimension of the e-governance process quality. The study also reinforced previous research findings in the B2C and B2B e-commerce domains, highlighting that e-service quality positively impacts online buyer's PV, SAT and ELOY.

This research contributed to the area of e-service operations by developing and validating the EMSQ model in the B2G e-commerce settings. Further, it has opened up new research avenues in B2G e-commerce.

The findings from this research highlighted that e-service operations managers should focus on usability, technological concerns, product/vendor quality concerns, customer support reliability, along with effective e-governance, ordering and logistics processes for e-business success. It also provides policymakers with guidelines for making B2G e-marketplaces sustainable.

To the best of the author's knowledge, this is the first study employing the GT and PLS-SEM techniques to explore EMSQ from the viewpoint of industrial buyers in B2G e-commerce. The study contributed to prior literature by proposing and validating the hierarchical EMSQ model.

Small business enterprises (SBEs) are a very critical element of the micro, small and medium enterprises (MSME) sector especially in the underdeveloped locations of the country. SBEs not only provide employment but also support the local economy by way of their products and services. In modern times, their presence on the digital platform is becoming essential and thus, these types of studies are required to bring to the table the issues and practices from the less represented sections of the sector. This study attempts to understand the responsiveness of the SBEs in Sikkim, India, and Bhutan in terms of their frequency of digital marketing (DM) usage. This study also attempts to understand the relationship between the factors affecting the practice or adoption of DM among the SBEs of Bhutan and Sikkim, India. For this purpose, empirical data were gathered from 320 SBEs from Sikkim and Bhutan representing the various sectors as defined by the national governments of the two countries. The SBEs of Bhutan and Sikkim are not found to be very active on the front of DM. The SBEs in these two locations need to become more active in using the digital platforms and tools to promote their products and services. The industry trends and government support in the form of infrastructural development are expected to play a vital role in orienting the SBEs into the adoption of DM in a better way. This study is crucial for the MSME sector, the government, telecom services providers, and local entrepreneurs.

AI-based chatbots are revamping employee communication in organizations. This paper examines the adoption of AI-based employee experience chatbots by employees.

The proposed model is developed using behavioral reasoning theory and empirically validated by surveying 1,130 employees and data was analyzed with PLS-SEM.

This research presents the “reasons for” and “reasons against” for the acceptance of AI-based employee experience chatbots. The “reasons for” are – personalization, interactivity, perceived intelligence and perceived anthropomorphism and the “reasons against” are perceived risk, language barrier and technological anxiety. It is found that “reasons for” have a positive association with attitude and adoption intention and “reasons against” have a negative association. Employees' values for openness to change are positively associated with “reasons for” and do not affect attitude and “reasons against”.

This is the first study exploring employees' attitude and adoption intention toward AI-based EEX chatbots using behavioral reasoning theory.