The Impact of Trade on Intra‐Industry Reallocations and Aggregate Industry Productivity

This paper develops a dynamic industry model with heterogeneous firms to analyze the intra‐industry effects of international trade. The model shows how the exposure to trade will induce only the more productive firms to enter the export market (while some less productive firms continue to produce only for the domestic market) and will simultaneously force the least productive firms to exit. It then shows how further increases in the industry's exposure to trade lead to additional inter‐firm reallocations towards more productive firms. The paper also shows how the aggregate industry productivity growth generated by the reallocations contributes to a welfare gain, thus highlighting a benefit from trade that has not been examined theoretically before. The paper adapts Hopenhayn's (1992a) dynamic industry model to monopolistic competition in a general equilibrium setting. In so doing, the paper provides an extension of Krugman's (1980) trade model that incorporates firm level productivity differences. Firms with different productivity levels coexist in an industry because each firm faces initial uncertainty concerning its productivity before making an irreversible investment to enter the industry. Entry into the export market is also costly, but the firm's decision to export occurs after it gains knowledge of its productivity.     

Interruption and Forgetting in Knowledge‐Intensive Service Environments

An increasing barrier to productivity in knowledge‐intensive work environments is interruptions. Interruptions stop the current job and can induce forgetting in the worker. The induced forgetting can cause re‐work; to complete the interrupted job, additional effort and time is required to return to the same level of job‐specific knowledge the worker had attained prior to the interruption. This research employs primary observational and process data gathered from a hospital radiology department as inputs into a discrete‐event simulation model to estimate the effect of interruptions, forgetting, and re‐work. To help mitigate the effects of interruption‐induced re‐work, we introduce and test the operational policy of sequestering, where some service resources are protected from interruptions. We find that sequestering can improve the overall productivity and cost performance of the system under certain circumstances. We conclude that research examining knowledge‐intensive operations should explicitly consider interruptions and the forgetting rate of the system's human workers or models will overestimate the system's productivity and underestimate its costs.     

Learning‐by‐Doing,Organizational Forgetting,and Industry Dynamics

Learning‐by‐doing and organizational forgetting are empirically important in a variety of industrial settings. This paper provides a general model of dynamic competition that accounts for these fundamentals and shows how they shape industry structure and dynamics. We show that forgetting does not simply negate learning. Rather, they are distinct economic forces that interact in subtle ways to produce a great variety of pricing behaviors and industry dynamics. In particular, a model with learning and forgetting can give rise to aggressive pricing behavior, varying degrees of long‐run industry concentration ranging from moderate leadership to absolute dominance, and multiple equilibria.     

The UK National Minimum Wage's Impact on Productivity

Low pay poses issues for managers internationally. We examine productivity in low‐paying sectors in Britain, since the introduction of the National Minimum Wage (NMW). We use a multiple channel analytical strategy, emphasizing the wage incentives channel and linking it to a model of unobserved productivity. We estimate firm‐specific productivity measures and aggregate them to the level of low‐paying sectors. Difference‐in‐differences analysis illustrates that the NMW positively affected aggregate low‐paying sector productivity. These findings highlight increased wage incentive effects with implications for management practice and public policy since ‘living’ wages may be productivity enhancing.     

绿色生产率及其对工业低碳发展的影响研究

基于1995年至2009年碳排放特征分组的中国工业投入产出数据,采用方向距离函数估算工业的生产效率和绿色生产率,基于方向距离函数的SML指数方法测算绿色生产率增长指数,从时间和行业两个维度比较分析工业绿色生产率的变化趋势和行业差异,结合改进的STIRPAT模型面板数据模型估计方法,就绿色生产率对工业低碳经济发展的作用及影响工业低碳发展的主要因素进行实证研究.研究结果表明,相对于不考虑碳排放的生产效率,绿色生产率在高碳排放强度行业上升,在低碳排放强度行业下降;绿色生产率先升后降,对工业低碳发展有显著正向影响,对高碳排放强度行业作用更大;绿色技术进步对工业绿色生产率增长和低碳经济发展的促进作用显著大于绿色技术效率;碳排放强度与经济产出关系具有U型曲线特征,化石能源结构调整不能促进工业低碳发展.     

The Impact of Investor Horizon on Say‐on‐Pay Voting

Shareholder investment horizons have a significant impact on say‐on‐pay voting patterns. Short‐term investors are more likely to avoid expressing opinion on executive pay proposals by casting an abstaining vote. They vote against board proposals on pay only in cases where the CEO already receives excessive pay levels. In contrast, long‐term investors typically cast favourable votes. According to our findings, this is due to effective monitoring rather than collusion with the management. Overall, investor heterogeneity in terms of investment horizons helps explain say‐on‐pay voting, in particular the low levels of say‐on‐pay dissent, which have recently raised questions over the efficiency of this corporate governance mechanism .     

The Impact of E‐Replenishment Strategy on Make‐to‐Order Supply Chain Performance

This research investigates the impact of electronic replenishment strategy on the operational activities and performance of a two‐stage make‐to‐order supply chain. We develop simulation‐based rolling schedule procedures that link the replenishment processes of the channel members and apply them in an experimental analysis to study manual, semi‐automated, and fully automated e‐replenishment strategies in decentralized and coordinated decision‐making supply chain structures. The average operational cost reductions for moving from a manual‐based system to a fully automated system are 19.6, 29.5, and 12.5%, respectively, for traditional decentralized, decentralized with information sharing, and coordinated supply chain structures. The savings are neither equally distributed among participants, nor consistent across supply chain structures. As expected, for the fully coordinated system, total costs monotonically decrease with higher levels of automation. However, for the two decentralized structures, under which most firms operate today, counter‐intuitive findings reveal that the unilateral application of e‐procurement technology by the buyer may lower his purchasing costs, but increase the seller's and system's costs. The exact nature of the relationship is determined by the channel's operational flexibility. Broader results indicate that while the potential economic benefit of e‐replenishment in a decentralized system is substantial, greater operational improvements maybe possible through supply chain coordination.     

Impact of Information Technology Integration and Lean/Just‐In‐Time Practices on Lead‐Time Performance*

Managers seeking to improve lead‐time performance are challenged by how to balance resources and investments between process improvement achieved through lean/just‐in‐time (JIT) practices and information technology (IT) deployment. However, extant literature provides little guidance on this question. Motivated by both practical importance and lack of academic research, this article examines empirically the relationships among interfirm IT integration, intrafirm IT integration, lean/JIT practices, and lead‐time performance using data from IndustryWeek's Census of Manufacturers ( IndustryWeek, 2006 ). The results provide several new insights on the relationship between IT integration and lean/JIT practices. First, the study confirms that implementing lean/JIT practices significantly reduces lead time. Second, lean/JIT practices mediate the influence of IT integration on lead‐time performance. This suggests that process improvements that result from lean/JIT practices are important contributors to the success of IT integration. Even companies that have experienced success in reducing lead time through lean/JIT practices may benefit from IT integration practices such as those embodied in enterprise resource planning systems. The findings provide managers with empirical evidence and a theoretical framework on the balance between lean/JIT and IT for effecting improvement in lead‐time performance, thus offering practical guidance on this important question. Future research is needed to extend the lean/JIT practices in this study to supply chain practices and explore the relationship between supply chain practices and IT integration.     

Effect of Learning and Forgetting on Batch Sizes

This paper investigates the effect of learning and forgetting on production scheduling decisions. Numerous papers have appeared on this topic in the last four decades; they show that firms are better off producing in larger batches in the presence of learning and forgetting. However, these papers fail to consider one or more of realistic features of learning and forgetting; factors such as (1) the amount forgotten increases with break length between two batches and (2) the forgetting could be slow over an initial short interval followed by fast forgetting. Our paper contributes by demonstrating that a consideration of these realistic features leads to a different conclusion—firms may be better off producing in smaller batches in the presence of learning and forgetting. This is a new insight that provides one more justification for producing in small batches.     

A Spatio‐Temporal Exposure‐Hazard Model for Assessing Biological Risk and Impact

We developed a simulation model for quantifying the spatio‐temporal distribution of contaminants (e.g., xenobiotics) and assessing the risk of exposed populations at the landscape level. The model is a spatio‐temporal exposure‐hazard model based on (i) tools of stochastic geometry (marked polygon and point processes) for structuring the landscape and describing the exposed individuals, (ii) a dispersal kernel describing the dissemination of contaminants from polygon sources, and (iii) an (eco)toxicological equation describing the toxicokinetics and dynamics of contaminants in affected individuals. The model was implemented in the briskaR package (b iological risk a ssessment with R ) of the R software. This article presents the model background, the use of the package in an illustrative example, namely, the effect of genetically modified maize pollen on nontarget Lepidoptera, and typical comparisons of landscape configurations that can be carried out with our model (different configurations lead to different mortality rates in the treated example). In real case studies, parameters and parametric functions encountered in the model will have to be precisely specified to obtain realistic measures of risk and impact and accurate comparisons of landscape configurations. Our modeling framework could be applied to study other risks related to agriculture, for instance, pathogen spread in crops or livestock, and could be adapted to cope with other hazards such as toxic emissions from industrial areas having health effects on surrounding populations. Moreover, the R package has the potential to help risk managers in running quantitative risk assessments and testing management strategies.     

The Impact of Mass Customisation on Manufacturing Trade‐offs

Management literature has suggested that the advent of mass customisation marks the end for trade‐offs between customisation and other competitive priorities (Pine et al. 1993; Westbrook and Williamson 1993; Tu et al. 2001). However, evidence supporting this proposition is anecdotal. This paper examines the impact of product customisation on four competitive priorities, drawing upon the results of a recent survey of 102 U.K. manufacturing firms from eight industry sectors. The study indicates significant compatibility between customisation and quality, volume flexibility, delivery reliability and non‐manufacturing costs. On the other hand, trade‐offs remain between customisation and manufacturing costs and delivery lead times. The results contradict the initial proposition that customisation can be “free,” and have important implications for firms embarking upon a mass customisation strategy.     

The Impact of Organizational Culture on Time‐Based Manufacturing and Performance

Firms are utilizing an array of manufacturing practices in their quest for survival and success in the marketplace. The implementation of those practices has not always resulted in success stories as the focus had been mostly on technical issues, with little concern for “soft issues.” For example, the enabling role of organizational culture has often been ignored. Using Schein's conceptualization of culture as underlying assumptions, espoused values, and artifacts, we examine a framework that relates culture and manufacturing practices to performance. The underlying assumption of customer orientation is posited to affect espoused values such as beliefs on investing in facilities and equipment to leverage intellectual work and to promote creativity, beliefs on working with others, beliefs on making decisions that are global, beliefs on management control, and beliefs on integrating with suppliers. The espoused values are hypothesized to affect visible attributes of culture (behaviors) such as time‐based manufacturing practices, which firms are employing for competitive advantage. A sample of 224 firms is used for developing research instruments and testing the hypothesized relationships advanced. Results indicate that high levels of customer orientation lead to a set of managerial beliefs that are collaborative and integrative. In turn, certain espoused values support a high level of time‐based manufacturing practice, which leads to high performance.     

Impact of Take‐Back Regulation on the Remanufacturing Industry

As waste from used electronic products grows steadily, manufacturers face take‐back regulations mandating its collection and proper treatment through recycling, or remanufacturing. Environmentalists greet such regulation with enthusiasm, but its effect on remanufacturing activity and industry competition remains unclear. We research these questions, using a stylized model with an original equipment manufacturer (OEM) facing competition from an independent remanufacturer (IR). We examine the effects of regulation on three key factors: remanufacturing levels, consumer surplus, and the OEM profit. First, we find that total OEM remanufacturing actually may decrease under high collection and/or reuse targets, meaning more stringent targets do not imply more remanufacturing. Consumer surplus and the OEM profit, meanwhile, may increase when OEM‐IR competition exists in a regulated market. Finally, through a numerical study, we investigate how total welfare changes in the collection target, what happens when the cost of collection is not linear, and what happens when IR products are valued differently by consumers.     

Knowledge Diversity,Turnover, and Organizational‐Unit Productivity: An Empirical Analysis in a Knowledge‐Intensive Context

We examine the role of knowledge diversity among unit members on an organizational unit's productivity. Utilizing a proprietary data set of corrective maintenance tasks from a large software‐services firm, we investigate the impact of two key within‐unit diversity metrics: interpersonal diversity and intrapersonal diversity. We analyze the independent influence of interpersonal diversity and the interactive influence of interpersonal diversity and intrapersonal diversity on organizational unit's productivity. Finally, we examine how diversity moderates productivity of an organizational unit when employee turnover occurs. Our analysis reveals the following key insights: (a) interpersonal diversity has an inverted U‐shaped effect on organizational unit's productivity; (b) intrapersonal diversity moderates the influence of interpersonal diversity on organizational‐unit productivity; (c) at higher levels of interpersonal diversity, rate of decrease in productivity of the organizational unit due to turnover is higher. We discuss the resulting theoretical and managerial insights associated with these findings.     

Misallocation and Total Factor Productivity in Italy: Evidence from Firm‐Level Data

Over the last two decades, total factor productivity (TFP) in Italy decreased by 0.2% per year, while increasing on average in the Euro‐area countries. This decline suggests the existence of large inefficiencies in the allocation of resources, making the Italian case particularly interesting and suitable in order to study the role of misallocation. In this article, I quantify the within‐industry misallocation of inputs in Italy over the period 1993–2011, by applying the Hsieh and Klenow's methodology. Using a micro‐level longitudinal dataset of Italian manufacturing firms, I find that, in the hypothetical absence of distortions, aggregate TFP in manufacturing would be boosted by 58% in 1993, by 67% in 2006 and by 80% in 2011. This leads to a twofold conclusion: first, misallocation plays a crucial role in determining the inefficiency level of the Italian manufacturing sector; second, misallocation has increased over time. Given the magnitude of the results obtained and the policy implications related thereto, I take a step ahead by checking to what extent the degree of misallocation can be attributed to specific characteristics of the Italian firms: it emerges that misallocation is higher for firms located in the south and at low‐technological intensity, as well as for small or young firms.     

Measuring Modularity‐Based Manufacturing Practices and Their Impact on Mass Customization Capability: A Customer‐Driven Perspective

As uncertainty in markets and technology intensifies, more companies are adopting modular product and process architectures to cope with increasing demands for individually customized products. Modularity‐based manufacturing is the application of unit standardization or substitution principles to create modular components and processes that can be configured into a wide range of end products to meet specific customer needs. This study defines modularity‐based manufacturing practices (MBMP), develops a valid and reliable instrument to measure MBMP, builds a framework that relates customer closeness, MBMP, and mass customization capability, and tests structural relationships within this framework using LISREL. Based on 303 responses from members of the Society of Manufacturing Engineers, statistically significant and positive relationships were found among customer closeness, modularity‐based manufacturing practices, and mass customization capability. Managerial implications of the empirical findings of this study and future research directions are also discussed.     

Product Differentiation,Multiproduct Firms,and Estimating the Impact of Trade Liberalization on Productivity

This paper studies whether removing barriers to trade induces efficiency gains for producers. Like almost all empirical work which relies on a production function to recover productivity measures, I do not observe physical output at the firm level. Therefore, it is imperative to control for unobserved prices and demand shocks. I develop an empirical model that combines a demand system with a production function to generate estimates of productivity. I rely on my framework to identify the productivity effects from reduced trade protection in the Belgian textile market. This trade liberalization provides me with observed demand shifters that are used to separate out the associated price, scale, and productivity effects. Using a matched plant–product level data set and detailed quota data, I find that correcting for unobserved prices leads to substantially lower productivity gains. More specifically, abolishing all quota protections increases firm‐level productivity by only 2 percent as opposed to 8 percent when relying on standard measures of productivity. My results beg for a serious reevaluation of a long list of empirical studies that document productivity responses to major industry shocks and, in particular, to opening up to trade. My findings imply the need to study the impact of changes in the operating environment on productivity together with market power and prices in one integrated framework. The suggested method and identification strategy are quite general and can be applied whenever it is important to distinguish between revenue productivity and physical productivity.     

The Impact of Complementary Agglomeration and Multi‐unit Systems on New Product Introduction

This study explores the relationship between organizational agglomeration and new product introduction. It proposes that product‐complementary agglomeration increases the likelihood of new product introduction, but that the effect on new product introduction is non‐linear. In addition, the influence of agglomeration on new product introduction is contingent on organizational form (i.e. multi‐unit form or independent form). Using longitudinal data for the hospital industry in Taiwan from 1997 to 2002, we found that the relationship between product‐complementary agglomeration and new product introduction is an upward trending hooked curve. As the degree of complementary agglomeration increases, the likelihood of introducing new products also increases, but the rate of increase diminishes with the degree of complementary agglomeration. In addition, we also found that the positive effect of product‐complementary agglomeration on new product introduction is stronger for independent firms than for multi‐unit firms.     

Quality‐related Action Programs: Their Impact on Quality Performance and Firm Performance

From analyses of the direct effects of 10 quality action programs on six firm performance outcomes, as well as their indirect effects through eight quality performance dimensions, two routes from action programs through quality performance to firm performance in the automotive supply industry are identified. The first is the product quality route, whose landmarks are superior quality performance on Conformance and Design Quality dimensions; the second is the relationship quality route, with superior Customer Responsiveness and Service. Both the product quality and the relationship quality routes lead to superior ROI; the former also leads to enhanced ROA, and the latter to enhanced market share performance. Associated key action programs are Committed Leadership, Cross‐Functional Quality Teams, Employee Empowerment, Supplier Development, and Closer Customer Relationships. The first three are internally focused, while the latter two are boundary‐spanning supply chain programs.     

The Impact of Revenue‐Maximizing Priority Pricing on Customer Delay Costs

Speed is an increasingly important determinant of which suppliers will be given customers' business and is defined as the time between when an order is placed by the customer and when the product is delivered, or as the amount of time customers must wait before they receive their desired service. In either case, the speed a customer experiences can be enhanced by giving priority to that particular customer. Such a prioritization scheme will necessarily reduce the speed experienced by lower‐priority customers, but this can lead to a better outcome when different customers place different values on speed. We model a single resource (e.g., a manufacturer) that processes jobs from customers who have heterogeneous waiting costs. We analyze the price that maximizes priority revenue for the resource owner (i.e., supplier, manufacturer) under different assumptions regarding customer behavior. We discover that a revenue‐maximizing supplier facing self‐interested customers (i.e., those that independently minimize their own expected costs) charges a price that also minimizes the expected total delay costs across all customers and that this outcome does not result when customers coordinate to submit priority orders at a level that seeks to minimize their aggregate costs of priority fees and delays. Thus, the customers are better off collectively (as is the supplier) when the supplier and customers act independently in their own best interests. Finally, as the number of priority classes increases, both the priority revenues and the overall customer delay costs improve, but at a decreasing rate.