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This paper presents an analytical framework for modeling and measuring strategic alignment. The resource-product-market (RPM) model is introduced as a means of representing the alignment of the firm's internal resources with its product lines and external markets. A strategic alignment index is defined to measure the degree of alignment represented by a model.

The RPM model is derived as an extension of prior research on diversification indexes. The strategic alignment index is mathematically defined and the properties of the model are characterized using graph theory. The approach is illustrated for two example firms.

The RPM model is flexible and can be used with different types and measures of resources, products and markets. The model represents strategy in a structural manner addressing a vertical type of alignment. The index ranges continuously from 0 to 1.0, providing a useful scale for measurement and comparison.

Practitioners may use RPM modeling to assess the current alignment of their respective firms and to identify strategic alternatives which increase alignment through a taxonomy of 13 strategic moves. The results of applying the model to ten firms are summarized.

The paper contributes to the literature by providing a new method for modeling firm strategy which integrates resource and industry views, thereby enabling a measurement of their alignment. The paper is also novel in the application of graph theory to management.

The purpose of this paper is to investigate risks faced by farmer cooperatives in China, using farmer cooperatives in Zhejiang province as a case. Specifically, the authors identify risks inherent in two primary types of farmer cooperatives in China (traditional and modern ones) when the external environment changes, the cooperative size expands and heterogeneity in membership widens.

The authors assume that the “uncertainty of the external environment” and the “deviation of organisational adaptation” constitute the two dynamic factors that generated risks for farmer cooperatives. A survey of 158 farmer cooperatives is obtained in Zhejiang province in 2010, and factor analysis is employed to identify the risks and their critical degrees of traditional and modern cooperatives.

The results indicate that two types of cooperatives in China face drastically different sets of risks. Traditional cooperatives face larger competitive and human resources risks, whereas modern cooperatives face larger decision-making and behavioural risks. Product market risk, macroeconomic policy risk and financial risk are common critical risks faced by both types of cooperatives.

In this paper, risks in China's farmer cooperatives were empirically studied and systematically discussed. The paper offers a typology to identify risks inherent in two primary types of farmer cooperatives in China (traditional and modern ones) according to property rights arrangements and governance structure.

The purpose of this paper is to explore empirically whether there are meaningful relationships between key entrepreneurial marketing (EM) variables and the demographic characteristics of the organization and its manager.

The data were gathered from a sample of 369 hotels from all regions of Thailand through the use of a postal survey. Several multiple regression models were used to test the relationships in the study. Interaction terms were added to some models to test the moderating effects of major demographic variables on various EM attributes.

The study shows which types of hotels and which types of managers were associated with EM characteristics. The results indicate that demographic characteristics, such as age, size, location, experience, and gender, significantly explain sets of entrepreneurial marketing variables. It was found, for instance, that both a young hotel and a large hotel are positively associated with entrepreneurial marketing, while owner management is positively associated with market orientation and negatively associated with growth aspirations but has no significant relationship with entrepreneurial orientation.

The paper provides a comprehensive overview of selected relationships between key EM dimensions in the existing literature. It is suggested that future research involves a more in‐depth exploration of some of the relationships found in this study.

As China emerges as a centre of manufacturing of the world, more and more small and medium sized enterprises (SMEs) start to outsource their production and related supply chain management in China. But it is very difficult to effectively manage the international outsourcing and supply chain mainly because their limited size and resources. International outsourcing agents emerge as a potential solution pursued by many western companies. Currently it has very limited information from both practical and theoretical aspects to understand the agents and their characteristics. This paper, based on four case studies of agents in three major industrial sectors in China, introduces business models and growth paths of the international manufacturing outsourcing agents, and establishes a set of key performance indicators (KPIs) for evaluation. The paper seeks to help western SMEs and hightech startups recognize the Chinese maturing and an ideal system for implementation, and to provide theoretical insights about the agents role and characteristics in international supply networks.

The purpose of this paper is twofold: first, to validate the global competitiveness project (GCP) framework in the Brazilian context; second, to describe the competitiveness levels on a sample of Brazilian firms, searching for heterogeneities of size, age and industry.

The study used the theoretical-empirical GCP framework, comprising the dimensions: human capital, product, domestic market, networks, technology, decision-making, competitive strategy, marketing, internationalization and online presence (Lafuente, Szerb and Rideg, 2016; Lafuente et al., 2019) and applied descriptive statistics, correlation analysis, confirmatory factor analysis and cluster analysis, on a survey data set of 55 Brazilian firms from different sizes, ages and industries.

The GCP framework was found robust, reliable and useful in emerging economies as the Brazilian. Three clusters of competitiveness were identified. Heterogeneities were detected in knowledge-intensive business services results. This work allows a better understanding of competitiveness through the identification and measurement of dimensions, which can help managers to identify/audit capacities to plan/improve firm performance.

Findings may support managers to identify, estimate and manage their competitiveness pillars, and thus increase their competitiveness levels with a focus on strategic long-term goals.

This paper contributes to knowledge production in two ways: to the validation of the framework in the Brazilian scenario and the understanding of the dynamics of competitiveness of firms.

This paper uses an organizational science framework to evaluate the present status of the public accounting profession and make recommendations for a systematic process to influence long‐term effective change. Historically, the profession has implemented short‐term responses to environmental events such as corporate merger mania, globalization of the economy, or demographic changes in the workforce. This paper suggests establishment of a joint long‐term effort among the Big Six firms as well as major national and regional firms to influence long‐term changes to the way the profession manages its human resources, develops and maintains businesses, and operates as a legal entity.

Resource-based view (RBV) theory (Barney, 1991; Barney and Mackey, 2016; Nagano, 2020) states that a firm’s tangible and intangible resources can represent a sustainable competitive advantage (SCA), a long-term competitive advantage that is extremely difficult to duplicate by another firm, when it meets four criteria (i.e. not imitable, are rare, valuable and not substitutable). In the context of this case, we believe there are three sources of SCA to be discussed using RBV – the major league soccer (MLS) team player roster, the use of artificial intelligence (AI) technologies to exploit this roster and the league’s single-entity structure: • MLS players: it has been widely acknowledged that a firm’s human resource talent, which includes professional soccer players (Omondi-Ochieng, 2019), can be a source of SCA. For example, from an RBV perspective, a player on the Los Angeles Galaxy roster: > cannot play for any other team in any other league at the same time (not imitable and are rare), > would already be a competitive player, as he is acquired to play in the highest professional league in the country (valuable) and > it would be almost impossible to find a clone player matching his exact talent characteristic (not substitutable) anywhere else. Of course, the roster mix of players must be managed by a capable coach who is able to exploit these resources and win championships (Szymanski et al., 2019). Therefore, it is the strategic human resource or talent management strategies of the professional soccer team roster that will enable a team to have the potential for an SCA (Maqueira et al., 2019). • Technology: technology can also be considered a source of SCA. However, this has been a source of contention. The argument is that technology is accessible to any firm that can afford to purchase it. Logically, any MLS team (or for that matter any professional soccer team) can acquire or build an AI system. For many observers, the only obvious constraint is financial resources. As we discuss in other parts of the case study, there is a fan-based assumption that what transpired in major league baseball (MLB) may repeat in the MLS. The movie Moneyball promoted the use of sabermetrics in baseball when making talent selection (as opposed to relying exclusively on scouts), which has now evolved into the norm of using technology-centered sports analytics across all MLB teams. In short, where is the advantage when every team uses technology for talent management? However, if that is the case, why are the MLB teams continuing to use AI and now the National Basketball Association (NBA), National Football League (NFL) and National Hockey League are following suit? We believe RBV theorists have already provided early insights: > “the exploitation of physical technology in a firm often involves the use of socially complex firm resources. Several firms may all possess the same physical technology, but only one of these firms may possess the social relations, cultural traditions, etc., to fully exploit this technology to implementing strategies…. and obtain a sustained competitive advantage from exploiting their physical technology more completely than other firms” (Barney, 1991, p. 110). • MLS League Single-Entity Structure: In contrast to other professional soccer leagues, the MLS has one distinct in-built edge – its ownership structure as a single entity, that is as one legal organization. All of the MLS teams are owned by the MLS, but with franchise operators. The centralization of operations provides the MLS with formidable economies of scale such as when investing in AI technologies for teams. Additionally, this ownership structure accords it leverage in negotiations for its inputs such as for player contracts. The MLS is the single employer of all its players, fully paying all salaries except those of the three marquees “designated players.” Collectively, this edge offers the MLS unparalleled fluidity and speed as a league when implementing changes, securing stakeholder buy-ins and adjusting for tailwinds. The “socially complex firm resources” is the unique talent composition of the professional soccer team and most critically its single entity structure. While every team can theoretically purchase an AI technology talent management system, its application entails use across 30 teams with a very different, complex and unique set of player talents. The MLS single-entity structure though is the resource that supplies the stability required for this human-machine (technology) symbioses to be fully accepted by stakeholders such as players and implemented with precision and speed across the entire league. So, there exists the potential for each MLS team (and the MLS as a league) to acquire SCA even when using “generic” AI technology, as long as other complex firm factors come into play.

This case relied on information that was widely reported within media, press interviews by MLS officials, announcements by various organizations, journal articles and publicly available information on MLS. All of the names and positions, in this case, are actual persons.

MLS started as a story of dreaming large and of quixotic adventure. Back in 1990, the founders of the MLS “sold” the league in exchange for the biggest prize in world soccer – the rights to host the 1994 Fédération Internationale de Football Association World Cup before they even wrote up the business plan. Today, the MLS is the highest-level professional men’s soccer league competition in the USA. That is a major achievement in just over 25-years, as the US hosts a large professional sports market. However, MLS has been unable to attract higher broadcasting value for its matches and break into the highest tier of international professional soccer. The key reason is that MLS matches are not deemed high quality content by broadcasters. To achieve higher quality matches requires many inputs such as soccer specific stadiums, growing the fan base, attracting key investors, league integrity and strong governance, all of which MLS has successfully achieved since its inception. However, attracting high quality playing talent is a critical input the MLS does not have because the league has repeatedly cautioned that it cannot afford them yet to ensure long-term financial sustainability. In fact, to guarantee this trade-off, the MLS is one of the only professional soccer leagues with an annual salary cap. So, the question is: how does MLS increase the quality of its matches (content) using relatively low cost (low quality) talent and still be able to demand higher broadcast revenues? One strategy is for the MLS to use AI playing technology to extract higher quality playing performance from its existing talent like other sports leagues have demonstrated, such as the NFL and NBA. To implement such a radical technology-centric strategy with its players requires the MLS to navigate associated issues such as human-machine symbioses, risking fan acceptance and even altering brand valuation.

The case is written and designed for a graduate-level (MBA) class or an upper-level undergraduate class in areas such as contemporary issues in management, human resource management, talent management, strategic management, sports management and sports marketing. The case is suitable for courses that discuss strategy, talent management, human resource management and brand strategy.