Search results

The direct selling model adopted in the beauty and cosmetics industry puts female consumer entrepreneurs at the heart of the business model. A neglected phenomenon in female entrepreneurship, this study aims to focus on female sales agents’ capabilities that are linked to sales performance and examine which capabilities might be shaped and enhanced through coaching and training in an emerging economy context.

Survey data were generated from a sample of 249 female sales agents who agreed to participate in a coaching and training programme run by a focal firm. Data were collected in two phases to investigate the capabilities linked to sales performance pre-intervention and the impact of coaching and training on the relationships between the capabilities and sales performance post-intervention. The time-lag data were analysed using partial least squares structural equation modelling.

For female sales agents, self-efficacy and sales experience have a significant positive effect on adaptive sales performance both before and after the coaching and training intervention. In contrast, intellectual capital and self-motivation had a non-significant relationship with sales performance before the intervention. However, after the intervention, the relationship between these variables became positive and significant.

The study demonstrates the effects of pre- and post-coaching and training on female consumer entrepreneurs’ capabilities and the links to sales performance. These findings add critical empirical knowledge on how female consumer entrepreneurship may be developed and the role of entrepreneurship for female empowerment in the Asian context. Collectively, the findings bring to the fore the female sphere in consumer entrepreneurship research in emerging economies.

This study aims to develop theory on the process toward digital service innovation (DSI) and to generate insights into how companies deal with the rising complexity associated with DSI, both inside and outside of the organization, through organizational learning and alignment.

After purposeful sampling, in-depth, longitudinal case studies of three manufacturers are presented as illustration. Per case, multiple semi-structured interviews are conducted, and insights are validated through rich additional data gathering. Each company's DSI pathway is reconstructed with critical incident technique. Next, using systematic combining, a middle-range theory is developed by proposing a theoretical frame concerning the relations between DSI maturity, learning and alignment.

The authors posit that, as companies gradually develop and progress toward DSI maturity, they deal with a rising degree of complexity, fueling their learning needs. Companies that are apt to learn, pass through multiple cycles of learning and alignment to overcome specific complexities associated with different DSI stages, with each cycle unlocking new DSI opportunities and challenges.

The study applies a stage-based view on DSI combined with complexity management and organizational learning and alignment theory. It offers a theoretical frame and propositions to be used by researchers for future DSI studies and by managers to evaluate alternative DSI strategies and implementation steps.

This study aims to address the global food waste problem in restaurants by analyzing customer sales information provided by restaurant tickets to gain valuable insights into directing sales of perishable products and optimizing product purchases according to customer demand.

A system based on unsupervised machine learning (ML) data models was created to provide a simple and interpretable management tool. This system performs analysis based on two elements: first, it consolidates and visualizes mutual and nontrivial relationships between information features extracted from tickets using multicomponent analysis, bootstrap resampling and ML domain description. Second, it presents statistically relevant relationships in color-coded tables that provide food waste-related recommendations to restaurant managers.

The study identified relationships between products and customer sales in specific months. Other ticket elements have been related, such as products with days, hours or functional areas and products with products (cross-selling). Big data (BD) technology helped analyze restaurant tickets and obtain information on product sales behavior.

This study addresses food waste in restaurants using BD and unsupervised ML models. Despite limitations in ticket information and lack of product detail, it opens up research opportunities in relationship analysis, cross-selling, productivity and deep learning applications.

The value and originality of this work lie in the application of BD and unsupervised ML technologies to analyze restaurant tickets and obtain information on product sales behavior. Better sales projection can adjust product purchases to customer demand, reducing food waste and optimizing profits.

Sales organizations embrace technological innovation. However, salespeople’s willingness to use new technology influences a firm’s return on investment, representing a significant concern for the organization. These concerns highlight tensions regarding the tradeoffs associated with technology implementations. The purpose of this study is to offer insights that help reduce the complexities of sales technology (ST) by exploring the changing dynamics of contemporary business relationships.

This paper synthesizes the ST literature using the service ecosystem perspective to propose the sales techno-ecosystem (STE) framework, providing new insights into organizational decision-making related to the ongoing digital transformation of sales tasks.

This synthesis of the ST literature with the service ecosystem seeks to clarify the impact of technology within the evolving nature of buyer–seller relationships by providing four unique perspectives.

Perspective 1 reviews the sales-service ecosystem framework and develops the theoretical underpinnings and relevant terminologies. Perspective 2 summarizes critical aspects of the ST literature and provides foundations for future research in the STE. Perspective 3 offers a more granular view, explicating roles and contexts prevalent in buyer–seller–technology interactions. Perspective 4 provides a set of tenets and advances research questions related to each tenet.

The culmination of these four perspectives is the introduction of five key tenants designed to help guide strategy and research.

The paper advances Hartmann et al. (2018) service ecosystem paradigm by explicating critical aspects of its ST domain to generate insights for theory and practice.

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.

This study aims to examine the applicability of Hartmann et al.’s (2018) service ecosystem framework to the day-to-day management of the modern sales force. The authors provide a review of the framework, acknowledging its strengths, while also indicating areas for advancement. The authors conclude with recommendations to the framework and indicate opportunities where future research could advance sales theory.

A review of the theoretical underpinnings of the service ecosystem framework is weighed against the established roles and responsibilities of the modern sales force in the literature.

The ability of the framework to capture the multi-level, multi-actor and dynamic aspects of sales represents an improvement in the conceptualization of selling is critical. Suggestions around the refinement for meso-level sales interactions and a more pliant application of service dominant-logic are offered.

The suggested extensions of the framework continue the advancement of novel theorization for the field of sales. Priorities for future research include consideration of ethical implications of the framework and formulations of new management strategies reflective of the broad and dynamic properties of the ecosystem conceptualization.

This paper provides managerial guidelines and implications tied specifically to the thick and thin crossing points and how they may impact employee decision-making.

To the best of the authors’ knowledge, this study is the first to pointedly examine the service ecosystem framework with respect to established principles of managing a modern sales force.

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 article focusses on the hybrid strategy, a simultaneous combination of cost leadership and differentiation strategy. The study aims to examine the impact of hybrid strategy on firm performance through its anticipated positive effects on process and product innovation. In addition, we study the moderating role of adaptive capacity in the direct relationships of hybrid strategy with process and product innovation.

Structural equation modelling was used to analyse 1,842 Spanish firms with fewer than 250 employees. We randomly selected small and medium-sized enterprises (SMEs) operating in Spain from the Spanish Central Business Directory (2021) database. The overall sample design was based on stratified sampling.

We found that hybrid strategy is positively related to firm performance and to process and product innovation. Additionally, in firms implementing hybrid strategies, process innovation fostered firm performance. Finally, adaptive capacity strengthened the relationships of hybrid strategy with process and product innovation. This sheds light on how and when hybrid strategy is most effective in fostering SME performance.

We highlight that SMEs need to establish strategies that use diverse resources and capabilities and not just generate competitive advantage using one strategy (cost leadership or differentiation strategy). This requires an agile and flexible systems and structures.

Our research provides novel results by proposing the adoption of hybrid strategies instead of pure strategies (cost leadership and differentiation strategy) as a way for SMEs to survive during crises. Unlike “stuck in the middle” strategies, our study demonstrates the importance of hybrid strategies in a comprehensive model that links them to innovation and firm performance, with adaptive capacity being a determining factor.

Today's marketing is dominated by decision-making based on artificial intelligence and machine learning. This study focuses on one semi- and unsupervised machine learning technique, generative adversarial networks (GANs). GANs are a type of deep learning architecture capable of generating new data similar to the training data that were used to train it, and thus, it is designed to learn a generative model that can produce new samples. GANs have been used in multiple marketing areas, especially in creating images and video and providing customized consumer contents. Through providing a holistic picture of GANs, including its advantage, disadvantage, ethical considerations, and its current application, the study attempts to provide business some strategical orientations, including formulating strong marketing positioning, creating consumer lifetime values, and delivering desired marketing tactics in product, promotion, pricing, and distribution channel. Through using GANs, marketers will create unique experiences for consumers, build strategic focus, and gain competitive advantages. This study is an original endeavor in discussing GANs in marketing, offering fresh insights in this research topic.

The purpose of this paper is to investigate the relationship between capabilities and renewal of organizational and business know-how in franchise networks.

This work uses a comparative case study of adaptive, absorptive and innovative capabilities to investigate knowledge renewal in 16 franchise networks.

The findings show that adaptive and innovative capabilities complement each other to foster know-how renewal. Furthermore, networks without internal R&D need to mobilize adaptive, absorptive and innovative capabilities to renew both organizational and business know-how. The findings also highlight that the three capabilities are interconnected.

The results of this research could provide insights for franchise networks to regenerate their knowledge base and ensure their long-term survival.

The underlying capabilities that explain organizational and business know-how renewal in franchises have not been investigated.