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The Bass model was created to analyse the product life cycle (PLC) in order to help sales and marketing departments in their business decision making. The purpose of this paper is to analyse the diferences between the clients assisted and sales variables, to discover which of the two variables is the more useful for the estimation of the PLC phases through the Bass model, thus aiding the managers of company sales and marketing departments.

In this research, the authors analysed the 223,577 clients assisted by a nationwide network of car dealerships, who acquired 36,819 vehicles, during a 24-month period. In the analysis, the Bass model was applied to define the PLC phases; and nonlinear regression models were used to carry out the estimations.

The results show that more consistent estimates of the PLC phases are obtained from the clients assisted variable. This work has theoretical and practical implications that can help business management.

The most remarkable thing about this research is that we have shown that the functionality of the clients assisted variable is greater than the sales variable for the Bass model and, therefore, for PLC estimation.

The results of this research are very useful, since they allow marketing decision makers to obtain more consistent estimations of the PLC phases using the Bass model and the clients assisted variable. This is based on the fact that the use of this variable helps to detect if there is any deficiency in the design of the marketing strategy when the client does not make the purchase.

The data on clients assisted are as easily available to companies as sales data. However, the use of this variable improves PLC analysis and this allows an improvement in company forecasting. Thus, making the clients assisted variable a tool to strategically plan investments in innovation and marketing would reduce uncertainty in business management.

The purpose of this paper is to analyse the diferences between the clients assisted and sales variables, to discover which of the two variables is the more useful for the estimation of the PLC phases through the Bass model, thus aiding the managers of company sales and marketing departments.

The purpose of this study is to investigate the influence of digital transformation on the intersection of marketing and sales departments.

This area has received little attention in academic literature while considerable amount of research exists surrounding the marketing and sales integration, the influence of the trend of digital transformation on both departments and how it affects their collaboration is not investigated in-depth and is therefore studied by qualitative research via semi-structured interviews in six German organizations.

By considering the findings the collaboration between the marketing and sales departments in German organizations is perceived as good. However, generation-related conflicts occur due to different demographic structures of employees. The study provides evidence that the digital transformation affects the marketing and sales integration and thus, the overall organizational performance.

Moreover, it is crucial that organizations face the challenges that occur in terms of interdepartmental relationships and be aware of the huge potentials which arise due to digital transformation to improve the marketing and sales collaboration.

This study examines the relationship between demand forecasting error and retail inventory management in an uncertain supplier yield context. Replenishment is segmented into off-season and peak-season, with the former characterized by longer lead times and higher supply uncertainty. In contrast, the latter incurs higher acquisition costs but ensures certain supply, with the retailer's purchase volume aligning with the acquired volume. Retailers can replenish in both phases, receiving goods before the sales season. This paper focuses on the impact of the retailer's demand forecasting bias on their sales period profits for both phases.

This study adopts a data-driven research approach by drawing inspiration from real data provided by a cooperating enterprise to address research problems. Mathematical modeling is employed to solve the problems, and the resulting optimal strategies are tested and validated in real-world scenarios. Furthermore, the applicability of the optimal strategies is enhanced by incorporating numerical simulations under other general distributions.

The study's findings reveal that a greater disparity between predicted and actual demand distributions can significantly reduce the profits that a retailer-supplier system can earn, with the optimal purchase volume also being affected. Moreover, the paper shows that the mean of the forecasting error has a more substantial impact on system revenue than the variance of the forecasting error. Specifically, the larger the absolute difference between the predicted and actual means, the lower the system revenue. As a result, managers should focus on improving the quality of demand forecasting, especially the accuracy of mean forecasting, when making replenishment decisions.

This study established a two-stage inventory optimization model that simultaneously considers random yield and demand forecast quality, and provides explicit expressions for optimal strategies under two specific demand distributions. Furthermore, the authors focused on how forecast error affects the optimal inventory strategy and obtained interesting properties of the optimal solution. In particular, the property that the optimal procurement quantity no longer changes with increasing forecast error under certain conditions is noteworthy, and has not been previously noted by scholars. Therefore, the study fills a gap in the literature.

This study established a two-stage inventory optimization model that simultaneously considers random yield and demand forecast quality, and provides explicit expressions for optimal strategies under two specific demand distributions. Furthermore, the authors focused on how forecast error affects the optimal inventory strategy and obtained interesting properties of the optimal solution. In particular, the property that the optimal procurement quantity no longer changes with increasing forecast error under certain conditions is noteworthy, and has not been previously noted by scholars. Therefore, the study fills a gap in the literature.

This paper aims to explore how and why salespeople enhance or hinder long-term business-to-business (B2B) customer relationships at the interpersonal level by considering self-disclosure and relational cost and reward evaluations.

Data from interviews (N = 47) with B2B sales professionals were analyzed, focusing on the shift of the phases in long-term B2B customer relationships.

Long-term B2B customer relationships evolve at the interpersonal level through a process of continuous relational cost and reward evaluation, self-disclosure and business disclosure in three phases: becoming business partners, collaborative partners and collaborative and personal partners. The reward evaluations progress from being business related to including even more relational benefits. Disclosure progresses through general business disclosure and general self-disclosure; strategic business disclosure and personal life self-disclosure; and synergistic business disclosure and private self-disclosure.

The long-term B2B customer relationships could be studied at the interpersonal level from the customer’s perspective. Self-disclosure could be studied in cross-cultural settings as well as gender differences should be considered in future studies. Business and social penetration theory could be applied to investigate different types of relationships and other professional relationships, such as those between employers and employees. It would be important to test whether the business-related and self-disclosure subtypes apply to the development of other types of professional relationships or whether other disclosure subtypes exist. The authors recommend exploring salespeople’s and customers’ privacy management strategies in multiple communication channels.

Managers may apply the results of this study in their customer relationship management and sales training.

The findings outline a contextual extension of social penetration theory.

The study aims to explore how concept stores (theoretically) differ from other experience-based retail formats, and hence, how they (practically) contribute to a diversified retail store portfolio.

Case study based on semi-structured, qualitative interviews with seven IKEA retail managers, three industry experts and 26 customers of IKEA concept stores in London and Stockholm.

The concept store represents a conceptual departure from other experiential store formats. It is neither fully experiential in the sense that it is not only about marketing communications nor is it sales or profit-focused. Its aim is to be an accessible touchpoint that reduces friction on a diversified customer journey with its value to the retail portfolio being that it attracts new and latent customers, mitigates existing inhibiting factors and drives them to other touchpoints.

Ideas about the different characteristics of new store formats and their potential to shape the customer experience are extended. New formats reflect innovation in retailing and are part of a retail portfolio which generates different customer expectations and determinants from traditional store formats which provide the customers' existing reference point.

The contributions of new formats should be evaluated in light of other existing formats in the portfolio and not isolated. This is particularly true when considering format cannibalisation and the potentially extended customer journey that arises when customers use traditional format stores and new concept format stores simultaneously.

Previous research, using sales metrics and market-based results as performance determinants, suggests negative outcomes for format diversification. Our study suggests that the contributions of the concept store format should be viewed from an overall customer journey perspective and the “performance” of different format based touchpoints are not best captured through traditional sales evaluation methods.

Smart services have gained attention both among academics and practitioners, but manufacturing firms struggle in getting their new smart services extensively adopted by customers, employees and distributors. The purpose of this paper is to identify and analyse the requirements of different actors and the interconnectedness between their requirements in introducing smart services.

An embedded single-case study was conducted with a manufacturing firm and its network, including its sales and service personnel, customers and external salespeople. Data were collected via 30 in-depth interviews.

The paper advances the multi-actor perspective by identifying the requirements of key actors for introducing smart services. These requirements were divided into eight categories: value of smart services, reliability of smart services, competence for smart services, data security and management, attitude towards services, reliance, knowledge of installed base of equipment and services and service reputation. The findings reveal the interconnectedness of different actors’ requirements for introducing new smart services and how discussion and relationships between actors affected their requirements.

The findings represent a comprehensive template of requirements, as well as mapping the interconnectedness of actors’ requirements, serving as a practical guideline for managers.

This study characterises the introduction of smart services as a multi-dimensional, interconnected effort by manufacturing firms and their networks. It shows that service introduction cannot be viewed as manufacturer’s development task or customers’ adoption decision only. Propositions are offered on how multiple actors’ viewpoints can be combined to achieve success in introducing smart services.

This study proposes a literature review and, based on the findings, the authors develop a conceptual framework, attempting to explain how technology may influence visitor behavior and eventually trade show performance.

The present research explores the role of visitors in the trade show context. The analysis specifically focuses on the variables that influence visitors’ participation at business-to-business trade shows and how their satisfaction and perception can be related to exhibition performance. The authors also take into consideration technological trends that prior to COVID-19 pandemics were slowly emerging in the trade show industry.

The findings highlight a continuity between pre-, at and postexhibition phases. Visitors’ behavior represents a signal of how a trade show is perceived as postexhibition purchases and next visit emerge as signals of an exhibition evaluation in relation to visitors’ perception. Besides being urgent tools for the continuity of the sector due to the pandemics, emerging technological trends can be key elements in understanding visitors’ behavior and in boosting their interest and loyalty toward trade shows.

The paper proposes a conceptual model including top notch and innovative technological trends to improve the understandment of visitors’ behavior. Both practitioners in companies and academics might find the study useful, given the digital uplift generated by the pandemics.

Digital platforms have enabled the emergence of new business models by transforming the competitive scenario, labour, traditional management activities and strategies of the organisations regarding a number of productive sectors. The objective of this study is to analyse these changes in the educational sector from the view of professors who produce content in digital platforms, such as the massive open online courses (MOOCs).

In-depth interviews were conducted with 10 Brazilian professors using MOOC. The methodology proposed by Bardin (2011) and the board’s guidelines (2013) were used for content analysis.

Positive aspects such as autonomy, higher financial gains, geographic coverage, quality of life and cheaper and quicker courses were identified in the present study, whereas negative aspects were disclosure and sales performed by faculty members, problems with technical support, demand for new skills (e.g. digital marketing), new teaching methods and opportunities perceived by the professors.

The results found cannot be generalised to different publics and contexts.

The results contribute to a better understanding of the new business models on digital platforms as they show evidence of how these techniques are contributing to digital transformation of traditional sectors. This model can be used to connect professors who produce content to those who want to learn as well as to enable remote operations in educational institutions. Additionally, managers, CEOs and entrepreneurs of the sector can use MOOC as a reference when formulating their strategies.

Contrary to the traditional technology project perspective, real estate investors see building-specific renewable energy (on-site energy) investments as part of the property and as something affecting the property’s ability to produce a (net) cash flow. This paper aims to show the value-influencing mechanism of on-site energy production from a professional property investors’ perspective.

The value-influencing mechanism is presented with a case study of a prime logistics property located in the Helsinki metropolitan area, Finland. The case study results are compared with the results of a survey answered by over 70 property valuation professionals in the Finnish real estate market.

Current valuation practice supports the presented value-creation mechanism based on the capitalisation of the savings generated by a building’s own energy production. Valuation professionals see benefits beyond decreased operating expenses such as enhanced image and better saleability. However, valuers acted more conservatively than expected when transferring these additional benefits to the cash flows of the case property.

Because the savings in operating expenses can be capitalised into the property value, property investors should consider on-site energy production when the return of on-site energy exceeds the return of the property. This enhances the profitability of on-site energy, especially in urban areas with low initial yields.

This is the first research paper to open the value-influencing mechanism of on-site energy production from a professional property investors’ perspective in commercial properties and to confirm it from a market study.