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This paper explores innovation adoption in inter-organizational healthcare networks. The authors develop theoretical speculations to investigate better the role of artificial intelligence (AI) as an innovative tool to improve buyer-supplier relationships, creating better performance outcomes.

The research is based on a theoretical investigation aiming at exploring the role of AI-based solutions for managing buyer-supplier relationships. The conceptual approach allows us to identify some research streams (e.g. co-working collaborations in supply chain management) by proposing a matrix that helps clarify the analysis's directions.

The results show the importance of AI that can help the operator in accessing supplier information, including current prices, available stocks, and delivery status, thereby reducing the risk of information asymmetry. AI is intended not only as a technology tool but also as an innovative solution to promote business relationships and support vertical alliances through the value chain between buyer and supplier.

This paper can help healthcare actors examine the choices behind their operational strategies by providing transparency of the activities and availability of information in real-time. Finally, our study reflects the future directions to enhance the cooperation and innovation adoption among healthcare operators.

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.

Increasing amount of empirical research in operations and supply chain management is using institutional theory as its theoretical lens. Yet, a common scale to measure the three institutional pressures – coercive, mimetic and normative – is lacking. Many studies use proxies or a single, grouped, construct of external pressures which present methodological challenges. This study aims to present the development of multi-item scales to measure institutional pressures (in a purchasing context).

First, items were generated based on the theoretical construct definitions. These items were then tested through academic sorting and an international survey. The first empirical testing failed to produce reliable and valid scales, and further refinement and analysis revealed that coercive pressure splits into two separate constructs. A second q-sorting was then conducted with purchasing practitioners, followed by another survey in Italy to verify the new measurement scale for four institutional pressures.

The multimethod and multistage measurement development reveals that empirically the three institutional pressures actually turn into four pressures. The theoretical construct of coercive pressure splits into two distinct constructs: coercive market pressure and coercive regulatory pressure.

The results of the paper, namely, the measurement scales, are an important theoretical and methodological contribution to future empirical research. They present a much-needed measurement for these theoretical constructs increasingly used in management research.

This paper aims to explore the role of configurations of relationship quality dimensions for explaining sources of behavioral outcomes in the globalized manufacturing industry.

A joint analysis of behavioral and objective performance data from globalized manufacturing links perceptual customer metrics that relate to dimensions of relationship quality (i.e. attitudinal loyalty, perceived customer orientation, customers’ perceived innovativeness of the supplier and perceived customer influence on supplier innovation) with behavioral outcomes (i.e. share of wallet (SOW) and customer account profitability). Using data from a global business-to-business (B2B) customer survey together with archival performance data from a multinational mechanical engineering firm, a fuzzy set qualitative comparative analysis (fsQCA) is performed.

The fsQCA results suggest that perceptual customer metrics related to innovation can be relevant aspects of relationship quality, in line with Anderson and Mittal’s (2000) satisfaction-repurchase-profitability chain framework and its adaptation to SOW. However, the underlying complexities in the different combinations of attributes in the recipe are such that they are not equifinal in leading to higher SOW or higher profitability. This paper finds indications for non-linearities between perceptual measures investigated and profitability of customer accounts, with particular relevance for the role of perceived customer orientation, perceived product innovativeness of the supplier and attitudinal loyalty.

The analysis faces a number of limitations, starting with its reliance on cross-sectional survey data, which does not enable us to account for feedback mechanisms, for example, arising from customer perceptions regarding innovation aspects. The lack of a multidimensional conceptionalization of the perceptual customer constructs may have limited the analysis, considering also recent evidence from retail companies in the furniture sector in Spain, suggesting that the multidimensional conceptualization of relationship value explained satisfaction and loyalty levels to a greater extent than the one-dimensional conceptualization (Ruiz-Martínez et al., 2019).

In terms of managerial implication, the results suggest that customers perceive limited value in participating in the focal firm’s innovation value chain funnel, hence customer loyalty cannot be bought using simple incentive strategies. The results with regard to customer account profitability suggest that B2B customers investigated here may distinguish when interacting with their globalized supplier in the innovation funnel: they may see a positive customer value when the innovation is a product, and thus, relation-specific, whereas they may see limited customer value when innovation is considered in more generic terms (customers’ perceived influence on supplier innovation in general).

This paper starts from the premise that perceptual customer metrics can matter for supplier performance, as the customer relationship and customer value management research has shown. However, there is limited empirical evidence from globalized manufacturing sectors incorporating perceptual constructs in behavioral outcomes, and limited evidence assessing customer-perceived value in such sectors through alternate approaches to main-effects focused analyzes. We employ qualitative comparative analysis using fuzzy sets (Russo et al., 2019) to address these gaps, focusing on two key behavioral outcomes, namely, customer account profitability and SOW.