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This paper deals with estimation of risk and the risk preference function when producers face uncertainties in production (usually labeled as production risk) and output price. These uncertainties are modeled in the context of production theory where the objective of the producers is to maximize expected utility of normalized anticipated profit. Models are proposed to estimate risk preference of individual producers under (i) only production risk, (ii) only price risk, (iii) both production and price risks, (iv) production risk with technical inefficiency, (v) price risk with technical inefficiency, and (vi) both production and price risks with technical inefficiency. We discuss estimation of the production function, the output risk function, and the risk preference functions in some of these cases. Norwegian salmon farming data is used for an empirical application of some of the proposed models. We find that salmon farmers are, in general, risk averse. Labor is found to be risk decreasing while capital and feed are found to be risk increasing.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO₂ emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.

The purpose of this paper is to examine the antecedents and performance consequences of voluntary information exchange between the production and sales functions.

Building on the motivation-opportunity-ability framework, the authors first posit a general model for bilateral information exchange across functional levels. The innovation presented in this model consists in allowing both sides of such an exchange (e.g. production-to-sales and sales-to-production) to differ in the perceived adequacy of information they receive. The two sides can also differ in terms of how their motivation and ability impact that adequacy. To test the model, the authors make use of survey responses and objective data from sales, production and executive managers of 182 Chinese manufacturers.

Analysis of the sample shows that the sales-to-production exchange has a smaller estimated performance effect than the production-to-sales exchange. Although shared opportunity is important in predicting both sides of the exchange, the measure of motivation appears to only significantly impact the sales-to-production exchange. In contrast, the measure of ability only appears to significantly affect the production-to-sales exchange.

Although limited to a regional context, differences in information-sharing drivers on the two sides of production-sales dyads pose strong implications that may be generalizable.

Specifically, these findings suggest alternative approaches and foci for resource investment that higher level managers can leverage in developing more effective cross-functional work settings.

This study differentiates itself from extant literature on information sharing by focusing on cross-functional (vs intra-functional) and voluntary (vs routine) information exchange.

The purpose of this paper is to analyze how important is co-location of R&D and production for firms originated from high-cost countries and to provide evidence of the relationship between the different strategies of location choices and co-location.

In order to investigate the relationship between R&D/design-production co-location and strategies of location choices for production, this paper uses a cluster analysis of 37 Italian firms that operate in fashion industry.

This article finds that co-location results in a dominant strategy for firms under the following conditions: high level of product customization, coordination difficulties between R&D and production, rapid change in production process technologies and product complexity difficult to be coded.

This paper presents some limitations in that it focuses only on fashion industry without considering other sectors.

This paper has some managerial implication in that offers some insight on decision making in organization. In particular offers some insights of how important is having an internal R&D/design function rather than collaborating with external designers in order to achieve competitive advantage in terms of product quality, product design and also brand name reputation.

This paper suggests that the co-location of R&D and production may improve the firms' performance considering the need for constant interaction between the two units. Moreover, it suggests that the co-location of R&D and production both within and external (within the firms' region and/or within the country) to the firms might be important. Furthermore, larger firms in terms of turnover have a greater preference to locate the R&D function close to the production function.

The main purpose of this paper is to introduce a comprehensive model explaining the global expansion of firms and to find out viable strategies for firms to survive global competition.

Through the critical review over existing literature, this study first introduces a new framework explaining the global expansion of firms at the level of functional activities in the value chain, and then empirically tests the predictions of the new framework with data in the motor industry.

Empirical findings confirm the new model's predictions. First, each function in the value chain has a unique way of global expansion: the global strategy is suitable for the production function, while the multidomestic strategy is applicable to the marketing function. Second, each function follows a dynamic path of global expansion from domestic to transnational via either global or multidomestic, according to the innate characteristics of corresponding function. Finally, the degree of global expansion of a firm is positively correlated with its financial performance.

Focusing on developing a new framework on global expansion, this study utilizes a rather small number of data and, therefore, requires readers' discretion when interpreting the results of statistical analyses.

With the dynamic diversification‐coordination model, managers can recognize the level and characteristics of their firms' global expansion, not only at the firm level but also at the functional level. This allows managers to establish a global strategy tailored to each function, thus reconciling possible conflicts generated from different interests among different functions in the firm.

First, this article introduces a new perspective of analyzing the global expansion of firms by shifting the level of analysis from the firm level to the functional level where the new framework can reconcile the constant debates on globalization. Second, this article suggests an intuitive and theory‐based index measuring the degree of global expansion of firms.

The purpose of this paper is to examine high-tech small-to-medium-sized enterprises (SMEs) supply chain partnerships. Partnerships are considered at the level of business function rather than the entire organisation. Second, the drivers of SMEs to engage in partnerships are assessed to see whether functions engage in partnerships for different reasons. Third, performance per function is assessed to see the differential effect of partnerships on the function’s performance.

In this study, the relationship between the drivers of SMEs to engage in partnerships, four types of partnerships (marketing and sales, research and development (R&D), purchasing and logistics, and production) and four types of functional performances of firms (marketing and sales, R&D, purchasing and logistics, and production) are examined. The data have been collected from 279 SMEs. The proposed hypotheses are tested using structural equation modelling.

The results indicate that there are considerable differences between business functions in terms of the degree of involvement in partnerships and the effect of partnerships on the performance of these functions. This paper contributes to research by explaining the contradictory results of partnerships on SMEs performance.

This study helps firms understand which type of partnership should be established based on the firm’s drivers to engage in supply chain partnership; and which partnership has a significant effect on which type of business performance of the firm.

The originality of this study is to investigate the relationship between different drivers to engage in supply chain partnership and different types of partnerships and different functional performance of firm in a single model.