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The purpose of the study was to benchmark meta-analytical conceptualizations of business-to-business (B2B) seller skills against empirical evidence in services firms.

The study is based on a deductive approach and questionnaire survey focusing on a range of services firms from different industries and corporate sizes. A total of 389 questionnaires out of 732 were returned, generating a response rate of 53.1%.

The study aims to provide empirical evidence and structures relating to B2B sellers' capabilities in a seven-dimensional conceptualization, all of which can be used in services firms to improve their seller efficiency. Each seller skill dimension performs a different function in the sales services process.

The authors conclude that the verified meta-analytical conceptualizations of B2B seller skills seem valid and reliable in services firms. Nevertheless, further research needs to be carried out, based on other company characteristics as well as industries.

It reduces the risk perceived by customers in B2B services settings through cultivating the sellers' capabilities, based on the seven-dimensional evidence of seller skills to enhance sales performance.

The study contributes to existing theory and previous studies by offering a foundation on which to structure sales performance indicators in services firms. Specifically, it contributes to structuring B2B seller skills across a selection of principal dimensions in B2B services settings.

The purpose of this study to improve the efficiency of customer acquisition and retention through the design of salary information disclosure mechanism.

This study develops a stylized game-theoretic model of delegating customer acquisition and retention, focusing on how firms choose delegation and wage information disclosure strategy.

The results confirm the necessity for enterprises to disclose salary information. When sales agents are risk neutral, firms should choose multi-agent (MA) delegation and disclose their wages. However, when agents are risk averse, firms may disclose the wages of acquisition agents or both agents in MA delegation, depending on the uncertainty of the retention market.

This paper contributes to the literature on delegation of customer acquisition and retention and demonstrates that salary disclosure can be used as a supplement to the incentive mechanism.

This study aims to explore how managers exercise agency in strategic investment decisions (SIDs) by drawing on their knowledgeability of the strategic context. Specifically, the authors address the role of position–practice relations and irresistible causal forces in this conduct.

The authors examine SID-making (SIDM) practices in four case organisations operating in highly competitive markets, conducting interviews with managers at various levels and analysing company documents. Drawing on strong structuration theory, the authors show how managerial decision makers draw upon their knowledge of organisational context when exercising agency in SIDs.

The authors provide insights into how SIDM behaviour, specifically agents’ conduct, is shaped by a combination of position–practice relations and the agents’ comprehension of their organisation’s context.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice. Particularly, the authors contribute to this literature by identifying irresistible causal forces and illuminating why actors might not resist in SIDM processes, despite having the potential to do so.

In most economies, there are rules from the market regulators or government to sell at an equal wholesale price (EWP). But when one upstream channel is facing a negative demand disruption and another positive, EWP can create extra pressure on the disadvantageous supply chain partner, which faces negative disruption. The purpose of this study is to analyse the impact of EWP and the scope of the discriminatory wholesale price (DWP) during disruptions.

For the study, the authors used a dual-channel supply chain consisting of a manufacturer, online retailer (OR) and traditional brick-and-mortar (BM) retailer. Stackelberg game is used to model the interaction between the upstream and downstream channel partners, and the horizontal Nash game to analyse the interaction within downstream channel partners. For modelling asymmetric disruption, the authors took instances from the lock-down and post-lock-down periods of the COVID-19 pandemic, where consumers flow from BM retailer to OR store.

By analysing the disruption period, the authors found that this asymmetric disruption is detrimental to the BM channel, favourable to OR and has no impact on the manufacturer. But with DWP, the authors found that the profit of the BM channel and manufacturer can be increased during disruption. Though the profit of the OR decreased, it was found to be higher than in the pre-disruption period. Under DWP, the consumer surplus increased during disruption, making it favourable for the customers also. Thus, DWP can aid in creating a win-win strategy for all the supply chain partners during asymmetric disruption. Later as an extension to the study, the authors analysed the impact of the consumer transfer factor and found that it plays a crucial role in the optimal decisions of the channel partner during DWP.

Very scant literature analyses the intersection of DWP and disruptions. To the best of the authors’ knowledge, this study, for the first time uses DWP as a tool to help the disadvantageous supply chain partner during asymmetric disruptions. The study findings will assist the government, market regulators and manufacturers in revamping the wholesale pricing policies and strategies to help the disadvantageous supply chain partner during asymmetric disruption.

In developing countries, how risk management technologies influence management accounting and control (MAC) practices is under-researched. By drawing on insights from institutional studies, this study aims to examine the multiple institutional pressures surrounding an entity and influencing its risk-based management control (RBC) system – that is, how RBC appears in an emerging market attributed to institutional multiplicity.

The authors used qualitative case study research methods to collect empirical evidence from a privately owned Egyptian insurance company.

The authors observed that in the transformation to risk-based controls, especially in socio-political settings such as Egypt, changes in MAC systems were consistent with the shifts in the institutional context. Along with changes in the institutional environment, the case company sought to configure its MAC system to be more risk-based to achieve its strategic goals effectively and maintain its sustainability.

This research provides a fuller view of risk-based management controls based on the social, professional and political perspectives central to the examined institutional environment. Moreover, unlike early studies that reported resistance to RBC, this case reveals the institutional dynamics contributing to the successful implementation of RBC in an emerging market.

Warranty-based big data analysis has attracted a great deal of attention because of its key capabilities and role in improving product quality while minimizing costs. Information and details about particular parts (components) repair and replacement during the warranty term, usually stored in the after-sales service database, can be used to solve problems in a variety of sectors. Due to the small number of studies related to the complete analysis of parts failure patterns in the automotive industry in the literature, this paper focuses on discovering and assessing the impact of lesser-studied factors on the failure of auto parts in the warranty period from the after-sales data of an automotive manufacturer.

The interconnected method used in this study for analyzing failure patterns is formed by combining association rules (AR) mining and Bayesian networks (BNs).

This research utilized AR analysis to extract valuable information from warranty data, exploring the relationship between component failure, time and location. Additionally, BNs were employed to investigate other potential factors influencing component failure, which could not be identified using Association Rules alone. This approach provided a more comprehensive evaluation of the data and valuable insights for decision-making in relevant industries.

This study's findings are believed to be practical in achieving a better dissection and providing a comprehensive package that can be utilized to increase component quality and overcome cross-sectional solutions. The integration of these methods allowed for a wider exploration of potential factors influencing component failure, enhancing the validity and depth of the research findings.

This paper aims to explore ChatGPT’s (generative pre-trained transformers) potential as a tool for retailers to improve customer experience and boost sales. While it provides benefits like personalized recommendations and 24/7 assistance, there are limitations, like difficulty in understanding unconventional language. The paper stresses careful integration to overcome these limitations and create a better customer experience. Additionally, it discusses the potential for further development and integration of ChatGPT in retail, such as generating product descriptions and virtual try-on experiences. Finally, the paper encourages retailers to embrace ChatGPT to meet their customer needs.

Case-based methodology involves using specific cases or examples to explore a broader issue or phenomenon. Researchers have analysed real-world cases to identify patterns, themes and insights that can be applied to other contexts or situations. This was useful for understanding complex and multifaceted issues as it allowed us to delve deeper into specific examples and explore the nuances of the situation.

While ChatGPT is a powerful tool for retailers, limitations such as difficulty in understanding non-standard accents and unconventional language can arise, causing customer frustration. Retail managers must integrate ChatGPT in a way that enhances customer experience. In the future, ChatGPT has the potential to generate product descriptions, provide virtual try-on experiences and integrate with augmented or virtual reality technology to offer more immersive experiences. Careful consideration and integration can help retailers overcome these limitations and offer personalized recommendations, round-the-clock assistance and an engaging customer experience that improves sales.

The case topic is very much in a novel stage of research and writing.

The primary objectives of the case study are to get the participants exposed to the issues of working capital which even profitable companies face on a day-to-day basis; give the participants an understanding of how to balance the, at times, conflicting objectives of increasing profits and sales through favorable credit terms; and expose them to the impact of increase in inventory levels and average collection period on margins in a period of slow growth. They will also learn about the concept of factoring and its uses.

The case study is about a group of companies engaged in education, steel fabrication and oil businesses owned by a single proprietor. The company was based in Fatehnagar which was part of Hyderabad district in the state of Telangana, India, and the case study traces the origins of the group from 1960s to 2021. The group was invested the surplus cash flows from the oil business to initiate and expand other businesses during this period. The economic downturn due to the COVID-19 pandemic had hit the company, particularly its oldest business – Noble Chemical Agency. The oil business was facing issues related to its growth and profitability, and the uncertainty around COVID-19-related restrictions had only augmented the fears of the management. The case study looks at issues and the dilemma which the owner of the company faced. The case study highlights various issues related to working capital management, especially related to receivables management and inventory levels faced by businesses during the slow-growth phase. It demonstrates how working capital management issues, if not resolved in time, can lead to insolvency of even a successful company with a sound business model.

The case study is meant for teaching in postgraduate management programs (Master of Business Administration and Postgraduate Diploma in Management) in the following courses: corporate finance/financial management course in the first year (the case study should be taught towards the end of the course); and management accounting courses in first year (the case study should be positioned in the middle of these courses). The case study can also be used to highlight issues related to working capital and small business management in a Management Development Programme (MDP) course for “Finance fundamentals for non-finance executives”.

Teaching notes are available for educators only.

CSS 1: Accounting and finance.

The purpose of this study is to provide an in-depth understanding of the B2B customers’ perspective regarding salespeople’s social media use.

The study adopts a qualitative approach based on semi-structured interviews with 26 key informants performing their job in customer role in various industries.

The authors inductively identify five themes regarding the B2B customers’ perspective of social media use in B2B selling. These themes allow for valuable implications for social selling activities and expected outcomes.

Against a growing body of literature on drivers, best practices and outcomes of social media use by B2B salespeople, less attention has been paid to the customer’s side. The authors extend current research by providing a more complete picture of social selling activities and expected outcomes.

This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation.

This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity.

This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers.

The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings.

This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS.

This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.