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This article is concerned with the role of theory in explaining the inter‐industry variation of vertical integration (VI). Why, for example, is the world aluminium industry highly integrated (Stukey, 1983) whereas the tin industry is not (Hennart, 1982)? The article is not concerned with explaining differences in the average level of VI across countries, although these are undoubtedly significant (Chandler and Daeins, 1980).

The purpose of this paper is to investigate the conditions under which working with an incumbent downstream competitor could be a beneficial strategy for upstream firms as the case of the relationship between banks and third-party payment providers.

Using a game model, this study considers a market with two upstream firms (banks) and two downstream firms (third-party payment providers). One downstream firm is an incumbent that poses a competitive threat to the upstream market, and the other downstream firm does not.

The results show that the optimal decision for banks depends on the number of loyal users the incumbent third-party payment providers and banks have. When the bank has more loyal users than the competitive third-party provider to a certain level, it would terminate cooperation with the provider; otherwise, the bank would maintain cooperation. This is true whether the duopoly banks are symmetrical or asymmetrical.

This study makes contribution to the theory of co-opetition lies in the fact that it examines a special case of competition and cooperation between vertical enterprises in the bank context. This study investigates how the upstream firms do when threatened by a downstream firm while the upstream firms have other options. This study also contributes to bank marketing theory through providing explanations for some of the incomprehensible cooperation in China's payment market, which is characterized by consumer loyalty. This study extends previous new-entry competition for banks by differentiating between incumbent and new-entry downstream firms.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJBM-11-2019-0414

This study aims to focus on the optimal green R&D of a capital-constrained supply chain under different channel power structures as well as the impact of capital constraint, financing cost, channel power structure and cost-reducing efficiency on green R&D and supply chain profitability.

A two-echelon supply chain is considered. The upstream firm engages in green R&D but has capital constraints that can be overcome by external financing. Green R&D is beneficial to reduce production costs and increase consumer demand. Based on whether or not the upstream firm is capital constrained and dominates the supply chain, four models are developed.

Capital constraints significantly lower green R&D and supply chain profitability. Transferring leadership from the upstream to the downstream firms leads to higher green R&D levels and downstream firm profitability, whereas the upstream firm's profitability is increased (decreased) if green R&D investment efficiency is high (low) enough. Greater financing costs reduce green R&D and downstream firm profitability; however, the upstream firm's profitability under the model in which it functions as the follower increases if the initial capital is sufficient. More importantly, empirical analysis based on practice data is used to verify the theoretical results reported above.

This study reveals how upstream firms in supply chains decide green R&D decisions in situations with capital constraints, providing managers and governments with an understanding of the impact of capital constraint, channel power structure, financing cost and cost-reducing efficiency on supply chain green R&D and profitability.

The major contributions are the exploration of supply chain green R&D by taking into consideration channel power structures and cost-reducing efficiency and the validation of theoretical results using practice data.

The purpose of this paper is to develop a new integrated approach for the strategic logistics outsourcing process through identifying the logistics independent success factors (ISFs) and linking them with the firm’s strategic objectives and logistics requirements. Then, the new integrated approach will be used to compare the outsourcing processes for the upstream and downstream supply chain members. Studies of logistics outsourcing reveal the strategic importance of this process and the increasing need for new strategic approach.

The design is based on mixed methodology and integrated approach. The fuzzy decision-making trial and evaluation laboratory technique has contributed to the construction of interdependent relationships, development of impact-relationship maps (IRMs) and identifying ISFs. The fuzzy quality function deployment technique was used to link the strategic objectives, logistics requirements and the ISFs to evaluate and select logistics service providers (LSPs) strategically. Finally, two case studies (upstream and downstream supply chains) are used to demonstrate the new approach effectiveness and to highlight the differences/similarities between the two streams.

In addition to the new strategic logistics outsourcing approach, this study analysed the impact relationships of the LSPs’ framework factors and constructed their maps. In all, 21 ISFs have been identified: 8 logistics key performance indicators, 7 logistics services and activities and 6 logistics resources and capabilities. The two streams’ comparison relived several differences in terms of strategic objectives, logistics requirements and ISFs.

The new approach for strategic logistics outsourcing can help firms to perform a better multi-stakeholder multi-criteria strategic outsourcing process. In addition, the upstream–downstream supply chain comparison increases our understanding how different supply chain members perform different outsourcing processes.

This is one of the pioneering studies that compares the supply chain upstream–downstream perspectives to highlight logistics outsourcing similarities and differences. To the best of author’s knowledge, this is one of the first logistics outsourcing studies that identifies ISFs for strategic logistics outsourcing, provides the first IRMs for the strategic logistics factors and develops a new integrated approach for strategic logistics outsourcing

The aim in this paper is to describe and explain the flexibility offered by different business models adopted by different firms as they strive to achieve higher levels of business performance.

Cross‐sectional research is used to investigate a matched pair sample of 20 high‐performing and 20 low‐performing firms in the UK. The relationship between business model architectures and focus are examined and their implications for flexibility are illustrated and discussed.

The flexibility offered by different business models is explored through the way organisations select and integrate three inter‐related elements to devise flexible business models, i.e. network influence, transactional relationships, and corporate ownership. Affected by situated practices in each business network and the market position or business size, companies select and integrate various configurations of these elements to respond to the constantly evolving demands of end‐customers.

Although based upon a cross‐sectional analysis of a matched pair sample, the concept of “flexible business models” has far wider managerial implications. The efficiency of the proposed approach is achieved through the reduction into three inter‐related elements that allow flexible configuration and re‐adjustment.

Companies can use the flexible business model approach to examine their own selection and integration of network influence, transactional relationships and corporate ownership and scrutinise their flexibility and performance in the marketplace.

The contribution of this paper is the development of the flexible business models concept, based on an empirical investigation of firms in the UK.

The purpose of this paper is to examine whether alliance portfolio R&D intensity contributes to biopharmaceutical firms' number of new product approvals and whether alliance portfolio R&D intensity is more positively related to the number of new product approvals for pharmaceutical firms than for biotechnology firms.

The paper employs a random effects Poisson regression model using panel data of 821 firm year observations for 146 biopharmaceutical firms operating in the USA. The robustness of results is also checked with additional analysis, provided in an appendix.

The results of this study show that the R&D intensity of firms' alliance portfolios is positively related to their new product introductions. It is also found that alliance portfolio R&D intensity has a more positive impact on the pharmaceutical segment of the industry's new product introductions than those of the biotechnology segment.

The authors develop and test theory about how the combined effects of two dimensions of alliance portfolio configuration (size and relationship strength) positively impact new product development. The authors propose a two dimensional alliance portfolio configuration measure, alliance portfolio R&D intensity. They combine the number of R&D alliances relative to the total number of alliances in the portfolio with the differential strength of ties associated with resource commitments required to source information from upstream and downstream alliances.

In today's globalized business environment, growing supply chain complexity (SCC) is arguably a major threat to the firm's business continuity with an adverse impact on the firm's competitive advantage and business performance. Researchers, though, investigated the impact of SCC drivers on a firm's operational performance, but the key question “Which supply chain complexity drivers severely impact the supply chain performance (SCP)?” remains largely unanswered from empirical research. The present study aims to decompose the SCC into four major constituting sub-categories (upstream, operational, downstream and external) to explore the causal impact of SCC drivers on SCP in direct and mediated manner.

The indicators applied for measuring constructs in the “Measurement model” are obtained from existing literature to increase the validity and reliability of the model. First, a pilot survey involving 25 SC managers from various manufacturing firms was conducted for indicator refinement and content validation. Second, the large-scale response data were collected through extensive surveys. This research explores the causality by testing the hypothesis applying Structural Equation Modeling (SEM) based on the responses received from 246 firms.

The study investigates the impact of SCC drivers on SCP through direct and mediation effect. The results indicate that upstream and operational SCC drivers play a mediating role in managing SCP. The findings reveal that upstream and operational SCC drivers adversely impact the SCP. Furthermore, the impact of downstream complexity on SCP is moderated through operational complexity drivers. The result explains the theoretical relation among SCC drivers supported by empirical validity.

The outcome offers practical relevance to supply chain (SC) managers in SCC and SCP management. Knowing the effect of SCC drivers among themselves and on SCP will facilitate the SC managers in devising the right strategies. The study provides a framework for prioritizing the resource in addressing the SCC issues among many.

The study addresses the apparent gap in the literature by modeling the impact of SCC drivers on SCP, which remained largely unexplored. First, it contributes to developing complex relationships among SCC drivers. Second, the direct and mediated causal effect of the SCC drivers individually and combinedly on SCP are explicated.

The purpose of this paper is to examine how contractor firms manage their relationships with extended supply chain tiers and investigate the range of ICT technologies used to facilitate such practices.

An on-line questionnaire survey was conducted to gather information about supply chain management operations, supplier relationship management and the ICT technologies used by contractor firms to manage their extended supply chain tiers.

The extended supply chain relationships of contractor firms are primarily composed of contractual, technical and financial entities, but findings suggest that the vision to consider extended supply chain firms when selecting suppliers are still myopic. Majority of ICT technologies are used between Tier 1 supply chain firms and there is an inconsistency in the number of technologies adopted with the extended supply chain tiers. Despite having a high involvement relationship with Tier 2 downstream firms, findings indicate a lack of use of ICT technologies to manage the organisational, personal and technological interactions with these firms.

On the basis of different relationship types this study develops an initial framework for management of supply chains that are facilitated by relevant ICT technologies.

This paper provides insights into the management of extended supply chain firms by contractor firms from a relationship-centric perspective and develops an initial framework for relationship-centric supply chain management.

This study aims to identify the types of relationships that intermediaries form with their suppliers and customers in the apparel supply chain and their implications for performance.

Cluster analysis was conducted on the supplier and customer relationships of 90 trade intermediaries in the apparel industry.

Three configurations were identified: moderately dependent relationships with suppliers and customers and moderate flexibility upstream; highly dependent relationships with suppliers and customers but low flexibility upstream; and relationships with suppliers and customers that are low in dependence. Performance of firms using these configurations differed. Firms that cultivated some dependence upstream and downstream performed best. Firms with highly dependent relationships with suppliers and customers but low flexibility upstream performed almost as well. This group was highly skilled in relationship management. Firms that maintained low dependence with suppliers and customers performed the worst.

Findings were based on a limited sample of 90 firms. Relationship configurations may differ in other industries, e.g. car industry.

For a supply chain to be effective, firms need to consider how they structure the relationships along the supply chain to facilitate the flow of information, goods and resources.

Prior research has considered relationships as independent dyads. This study looks at tripartite relationships involving suppliers and customers in the supply chain.

This study aims to explore the dependence structure among Chinese firms across the emerging 5G industry at different stages and to provide some strategic insights for market participants.

This study adopt macroeconomic fundamentals and the log-returns of 45 listed firms in the Chinese 5G industry to construct the weighted adjacency matrix by measuring the correlation parameters and then use the triangulated maximally filtered graph (TMFG) algorithm to construct the dependence network. It analyses the topological structure of the constructed networks to obtain the dependence characteristics for each firm in the whole industrial supply chain at different levels.

The empirical results provide a comprehensive and concise snapshot of the industrial structure, across the whole 5G industry at different levels, rather than just a “one-to-one” pattern. Specifically, the dependence characteristics of different firms are heterogeneous, and most firms are highly connected with partners in the whole industrial supply chain, whereas a few firms that are weakly connected. Those closely connected firms are usually in the midstream. In addition, compared with firms at different levels, downstream firms usually have closer dependencies and stronger influence capabilities.

Regulators not only should promote stability development for those firms most intensely connected with whole industry chain but also protect those firms with weak link in the whole industry chain. Investors should better understand the embedded ties among different firms to obtain effective market information and can select multiple firms with fewer connections as backup to conduct joint investment for risk mitigation. Mangers should give priority to the central players/firms in the whole industrial supply chain and establish the alliances with closely connected firms.

This study contributes to both the information system and operation management literature by constructing a new network method, Copula-TMFG, to capture the dependence structure among Chinese firms in 5G industry, empirically providing some strategic insights for 5G industry stakeholders, such as regulators, investors and managers.