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This paper empirically demonstrates the major organizational events of a rolling forecasting process and the roles of controllers therein. In particular, this study aims to investigate how the understanding of a “realistic forecast” is translated and questioned by various mediators in the rolling forecasting process and how it affects the quality of planning as the ultimate accuracy of forecasts is seen as important.

This study follows an actor-network theory (ANT) approach and maps the key points of translation in the rolling forecasting process by inspecting the roles of mediators. This qualitative case study is based on interviews with controllers and managers involved in the forecasting process in a single manufacturing company.

The paper identified two episodes of translation in the forecasting process, in which the forecast partially stabilized to create room for managerial discussion and debate. The abilities of controllers to infiltrate various functional groups and calculative practices appeared to be one way to control the accuracy of forecasting, although this was built on a façade of neutrality.

Prior literature identifies the aims of interactive planning processes as being to improve the quality of planning. The authors apply ANT to better understand the nature of mediators in constructing an entity called a “realistic rolling forecast”.

This paper aims to investigate whether professional data analysts’ trust of black-box systems is increased by explainability artifacts.

The study was developed in two phases. First a black-box prediction model was estimated using artificial neural networks, and local explainability artifacts were estimated using local interpretable model-agnostic explanations (LIME) algorithms. In the second phase, the model and explainability outcomes were presented to a sample of data analysts from the financial market and their trust of the models was measured. Finally, interviews were conducted in order to understand their perceptions regarding black-box models.

The data suggest that users’ trust of black-box systems is high and explainability artifacts do not influence this behavior. The interviews reveal that the nature and complexity of the problem a black-box model addresses influences the users’ perceptions, trust being reduced in situations that represent a threat (e.g. autonomous cars). Concerns about the models’ ethics were also mentioned by the interviewees.

The study considered a small sample of professional analysts from the financial market, which traditionally employs data analysis techniques for credit and risk analysis. Research with personnel in other sectors might reveal different perceptions.

Other studies regarding trust in black-box models and explainability artifacts have focused on ordinary users, with little or no knowledge of data analysis. The present research focuses on expert users, which provides a different perspective and shows that, for them, trust is related to the quality of data and the nature of the problem being solved, as well as the practical consequences. Explanation of the algorithm mechanics itself is not significantly relevant.

This study aimed to examine the digital transformation of business-to-business (B2B) sales and its effects on the management of value-based selling.

The study adopted a qualitative interview research design. A total of two participant groups—one consisting of sales management professionals and the other consisting of buyers—were created to conduct abductive data analysis to gain a new understanding of B2B sales management.

As a result of the digital transformation of sales, companies are shifting B2B sales towards value-based selling using a more proactive, continuous process wherein digital value co-creation activities play a big role. Similarly, their buyers now expect more proactive communication about new value propositions, but social media channels are of little importance to most B2B buyers. The management of digital value co-creation activities should be addressed from the sales ecosystem perspective, where non-sellers tend to have a strong role in communicating new value propositions.

There needs to be further research on digital value co-creation activities in the sales ecosystem, as value-based selling requires that selling organizations focus more on educational digital content marketing and engagement with non-sellers via both marketing and sales activities.

Companies rarely exploit experts and project personnel when implementing digital sales strategies; however, they often meet with customers personally and network with them. This requires a broader perspective on sales management.

This is one of the first studies to explore the management of value-based selling from both seller and buyer perspectives.

This study aims to investigate how business-to-business (B2B) companies build brand personality via the products they provide and via their interactions with customers.

A multiple case study, which spans 10 years, investigates via interviews, observations, workshops and document analysis how two fast-growing B2B companies selling industrial equipment to manufacturers build brand personality.

The studied companies concentrate on different brand personality dimensions depending on the activities in which they engage. By focusing on brand competence in the realm of the actual product and brand warmth in the realm of the augmented product, the companies manage to create a complete and consistent brand personality.

The research approach provides in-depth knowledge on how the companies build brands for a specific type of B2B product. However, the article’s perspective is limited to that of management and therefore does not take customer reactions into account.

The study describes how firms can build strong B2B brands by emphasizing competence in product design and R&D and warmth in activities related to sales and customer service.

The study introduces a conceptually consistent view of brand personality in the form of warm and competent brands to the B2B marketing literature. It builds on and contributes to the emerging research on B2B brand personality. By relating the companies’ brand-building activities to the type of products they sell, this study illustrates how context affects B2B brand building, and by integrating brand personality theory with product levels and marketing philosophy, it extends previous theory on B2B branding.

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.

The military of today depends on the availability and readiness of high-technology weapon systems. As the military often has to focus on core tasks (the usage of systems), logistics and support tasks are outsourced to industry, which means that industrial suppliers gain importance for making weapon systems available and mission ready. However, companies are profit-maximizing and invest their best resources in the most promising business areas, which might be clients other than the (domestic) military customer. This raises the question of how the military can ensure that the defense industry provides the best performance: preferential treatment for the military. The purpose of this study is to investigate preferential treatment in the specific context of defense.

This paper reports on the examination of factors influencing preferential treatment for the military. The analysis uses structural equation modeling and data from a sample of German defense suppliers.

The results show that the perceived customer attractiveness has a strong effect on preferential customer treatment. Attractiveness is influenced by trust, commitment and a comparison with other customers.

There are several implications for defense theory and practice, including the need for further consideration of relational in contrast to transactional practices in military–industrial supply collaboration, as these seem highly relevant for getting the best resources for producing and maintaining weapon systems. In addition, increasing customer attractiveness, in particular if the military lacks a domestic defense industry base, is proposed.

The findings are based on a focus sample of only defense suppliers. This paper transfers the industrial discussion about the buyer–supplier relationships and preferential customer treatment to the defense logistics research context.