Longevity and Cultural Differences of International Joint V entures: Toward Time-Based Cultural Management

This article explores the relationships amongtime, organizational, and national cultural distance inan international joint venture setting. Moreparticularly, the extent to which the longevity of aninternational joint venture affects the intensity of itscultural differences, is investigated in a sample of 51international joint ventures set up in Hungary. Itaddresses certain mechanisms available to aninternational joint venture's managers and to its partners todeal with cross-cultural issues. The results suggestthat the temporal dimension is a cultural moderator ofprime importance, but to be totally effective, it must be combined with a willful strategy ofcultural integration.     

Go and Say, “We're Shutting”: Ju Jutsu as a Metaphor for Analyzing Resistance

While it is well known that employees inorganizations may successfully resist managerialimpositions, relatively little is understood about howresistance operates. The present study utilizes amartial arts metaphor known as ju jutsu to generateinsights for understanding how resistance is exercised.The ju jutsu metaphor was chosen because it is adefensive technique whereby a physically weaker person may resist a much stronger one. Ju jutsu asmetaphor suggests resistance can be exercised bysystematically employing bodily movements which disturban opponent's balance and/or strike at physiological weak points. By exploring a case study of asuccessful example of organizational resistance, the jujutsu metaphor is utilized to generate new perspectivesfor conceptualizing and analyzing the dynamics of resistance.     

UPSTREAM VOLATILITY IN THE SUPPLY CHAIN: THE MACHINE TOOL INDUSTRY AS A CASE STUDY

Cyclicality is a well‐known and accepted fact of life in market‐driven economies. Less well known or understood, however, is the phenomenon of amplification as one looks “upstream” in the industrial supply chain. We examine the amplification phenomenon and its implications through the lens of one upstream industry that is notorious for the intensity of the business cycles it faces: the machine tool industry. Amplification of demand volatility in capital equipment supply chains, e. g., machine tools, is particularly large relative to that seen in distribution and component parts supply chains. We present a system dynamics simulation model to capture demand volatility amplification in capital supply chains. We explore the lead‐time, inventory, production, productivity, and staffing implications of these dynamic forces. Several results stand out. First, volatility hurts productivity and lowers average worker experience. Second, even though machine tool builders can do little to reduce the volatility in their order streams through choice of forecast rule, a smoother forecasting policy will lead companies to retain more of their skilled work force. This retention of skilled employees is often cited as one of the advantages that European and Japanese companies have had relative to their U. S. competitors. Our results suggest some insights for supply chain design and management: downstream customers can do a great deal to reduce the volatility for upstream suppliers through their choice of order forecast rule. In particular, companies that use smoother forecasting policies tend to impose less of their own volatility upon their supply base and may consequently enjoy system‐wide cost reduction.     

IMPROVING POM LEARNING: SYSTEMS THINKING AND TRANSPARENT-BOX BUSINESS SIMULATORS

It is well known by systems thinkers that the behavior of complex systems (for example, the company as a whole or the operations subsystem) depends upon their structure (the set of system variables and their interrelationships). In our opinion, the methods and tools presently used for production and operations management (pom) teaching are insufficient to cope with an ever more complex reality. Over the last few years, the research group GIdEao, following an original idea (Machuca 1992a, 1992b) has been developing transparent-box business simulators (TBBSS) based on systems thinking and system dynamics models; the aim was to maintain the advantages of the existing didactic tools while mitigating their drawbacks. The most distinctive feature of TBBSS (as opposed to the traditional black-box business games) is that the structure of the system to be simulated is always accessible to the users, who can thus reflect on the causes underlying the results obtained and thereby improve decision-making and the learning process. We will show how to work with TBBSS, and we will comment on the results obtained in an empirical experiment which aims to measure the influence of TBBSS on the learning process.     

A TUTORIAL ON BOTTLENECK DYNAMICS: A HEURISTIC SCHEDULING METHODOLOGY

We give a tutorial on bottleneck dynamics. Bottleneck dynamics is a scheduling framework that uses approximate dual resource prices to make decentralized decisions. The basic idea is to establish a price for a resource as a function of the set of jobs that need to be processed by the resource. Tasks are then sequenced according to a cost/benefit ratio. Starting with one resource sequencing problems, we describe how priorities for jobs can be developed and how they translate into resource prices. We then describe how resource prices can be approximated in a multiresource situation and how lead times which are critical for these approximations can be accurately computed. We also describe a number of studies that have shown bottleneck dynamics to be an effective approach in several different problem areas.     

Exploring the joint dynamics of intercity internet and corporate networks: a stochastic actor‐based modelling approach

In this article, I show one possible solution to synthesis dynamics in multiple intercity networks. I adopt a stochastic actor‐based modelling approach to explore the co‐evolution of an intercity corporate network of 57 globalized advanced producer service firms across 93 cities, and another intercity internet network between these 93 cities, for the period 2004–2010. Stochastic actor‐based models (SABMs) help to connect interactions among cities and firms on the local scale with empirically observed networks on the global scale. My analysis accounts for the co‐evolution/interdependence among multiple world city networks (WCNs) and associated network changes in individual WCNs with exogenous city‐related covariates and endogenous local network structures.