Dynamic Analysis for Enterprise Strategic Flexibility using System Engineering Methodology

From a system thinking perspective, the competition / cooperation boundaries govern the evolution of a firm\u27s adaptive strategic behaviour and drive it towards its desired objectives. Strategic flexibility is considered a sustainability advantage in today\u27s global competitive environment. This study explores the strategic flexibility capability that fits with the market requirement and the degree of competition it faces in its market(s). After exploring the link between the manufacturing objectives and their effect on the total industry performance in terms of profitability, product availability and capacity utilization, this study quantify the strategic effect of applying five different strategies on the enterprise strategic flexibility capability. By modeling and analyzing different scenarios using a system dynamic simulation approach and considering the market competitive dynamics, this model introduces the volume flexibility as a macro strategic measure that affects the firm\u27s intended production capacity. The effect of enterprise volume flexibility on its market share is studied and reported. The research explored how operations management theory on volume flexibility can be linked to the dynamic capability theory to develop new macro measures for the enterprise manufacturing strategy. Results show that matching between the firm capabilities and its external environment is a critical factor for organizational success. While the intense of competition govern the product life cycle duration and rate of change, success level is proportional to the competitor simultaneous actions and reactions and the effect differs from market to another. Results show that different product life cycle affects the industry speed and that may change the wining strategies adopted by the competing firms. As a result there are no ultimate right strategies for firms to follow. While tradeoffs between flexibility and cost are confirmed, the competitive advantage occurs when it is unique to the company and matches with the market variables for limited time. In conclusion, for industrial organization to achieve high productivity, efficiency and maximum utilization rate they need to select from a wide range of strategic capabilities rather than concentrating on a single capability or process to match the requirements of the external environment with responsive rate that matches the industry clock speed

Centralized Supply Chain Network Ddesign: Monopoly, Duopoly, and Ooligopoly Competitions under Uncertainty

This paper presents a competitive supply chain network design problem in which one, two, or three supply chains are planning to enter the price-dependent markets simultaneously in uncertain environments and decide to set the prices and shape their networks. The chains produce competitive products either identical or highly substitutable. Fuzzy multi-level mixed integer programming is used to model the competition modes, and then the models are converted into an integrated bi-level one to be solved, in which the inner part sets the prices in dynamic competition and the outer part shapes the network cooperatively.Finally, a real-world problem is investigatedto illustrate how the bi-level model works and discuss how price, market share, total income, and supply chain network behave with respect to key marketing activities such as advertising, promotions, and brand loyalty

The Flexibility and Specialization of Resources - Competitive Strategies of Materials Decoupling Points of a Network Supply Chain of Metallurgic Products

AbstractThe configuration of the supply chain which realizes the postponed production strategy, requires consideration of the issue of formation of network relations in order to increase the supply potential. The increase in the number of network relations shaped by materials decoupling point of the supply chain can be a consequence of an endeavour to reduce the logistic costs, improvement in the level of the customer service or an increase in innovativeness. In the model presented in the article the authors considered the issue of reducing logistic costs with the established high level of the customer service, taking into account the problem of the flexibility of resources

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Understanding and Leveraging Crowd Development in Crowdsourcing

abstract: Although many examples have demonstrated the great potential of a human crowd as an alternative supplier in creative problem-solving, empirical evidence shows that the performance of a crowd varies greatly even under similar situations. This phenomenon is defined as the performance variation puzzle in crowdsourcing. Cases suggest that crowd development influences crowd performance, but little research in crowdsourcing literature has examined the issue of crowd development. This dissertation studies how crowd development impacts crowd performance in crowdsourcing. It first develops a double-funnel framework on crowd development. Based on structural thinking and four crowd development examples, this conceptual framework elaborates different steps of crowd development in crowdsourcing. By doing so, this dissertation partitions a crowd development process into two sub-processes that map out two empirical studies. The first study examines the relationships between elements of event design and crowd emergence and the mechanisms underlying these relationships. This study takes a strong inference approach and tests whether tournament theory is more applicable than diffusion theory in explaining the relationships between elements of event design and crowd emergence in crowdsourcing. Results show that that neither diffusion theory nor tournament theory fully explains these relationships. This dissertation proposes a contatition (i.e., contagious competition) perspective that incorporates both elements of these two theories to get a full understanding of crowd emergence in crowdsourcing. The second empirical study draws from innovation search literature and tournament theory to address the performance variation puzzle through analyzing crowd attributes. Results show that neither innovation search perspective nor tournament theory fully explains the relationships between crowd attributes and crowd performance. Based on the research findings, this dissertation discovers a competition-search mechanism beneath the variation of crowd performance in crowdsourcing. This dissertation makes a few significant contributions. It maps out an emergent process for the first time in supply chain literature, discovers the mechanisms underlying the performance implication of a crowd-development process, and answers a research call on crowd engagement and utilization. Managerial implications for crowd management are also discussed.Dissertation/ThesisDoctoral Dissertation Business Administration 201

On the Evolution of Trading Institutions: The Platform Design Paradox

This paper analyzes a learning model where sophisticated market designers create new trading platforms and boundedly rational traders select among them. We ask wether "Walrasian'''' platforms, leading to efficient (market - clearing) trading outcomes, will dominate the market in the long run. If several market designers are competing, we find that traders will learn to select non-market clearing platforms with prices systematically above the market-clearing level, provided at least one such platform is introduced by a market designer. This in turn leads all market designers to introduce such inefficient (non-market clearing) platforms. Hence platform competition induces non-competitive market outcomes.economic systems ;

Diffusion of agile supply chains attributes: a study of the UK upstream oil and gas industry cluster

This study examines agile supply chain capabilities in oil and gas clusters, in the light of cluster and industrial district theory. The aim is to provide evidence of their potential impact on competitiveness and business performance within the UK upstream oil and gas cluster. Agility is the ability of organisations to operate and prosper in market conditions characterised by dynamism and constantly changing customer tastes. Clusters and industrial districts refer to the geographic concentration of firms in an industry that enables the firms to benefit from competition and cooperation as well as enhanced productivity within the cluster.A review of past theoretical and empirical studies on supply chain management, agility and clusters identifies four dimensions of agility: customer enrichment, cooperating to compete, mastering change and uncertainty, and leveraging the impact of people and information. The cluster theory points to the competitive advantage of being in geographic proximity to the members of a supply chain, including enhanced productivity, easy access to enriched and high quality factors of production, reduction of transaction and transportation costs as well as increased innovativeness. These all contribute to improving the competitive capability of a firm as well as having impact on the business performance of organisations. A survey of 880 firms in the UK upstream oil and gas cluster was conducted to determine the specific impact of cluster location attributes on the agility of supply chains. Six case studies involving the three tiers of the supply chain and supporting organisation were carried out.Structural equation modelling revealed strong impact of clusters on competitive objectives but weak impact on business performance. Results from the survey show that cluster agility has strong impact on both competitive objectives and business performance. The case study revealed that agility is a strategic tool adopted by the smaller organisations within the supply chain to mitigate the scale of large organisations. Equally, SMEs consider that being in UK oil and gas cluster enhances their responsiveness

Value Creations Through Co-Creation and Collaboration Strategy in SMEs Creative Industry

The study focuses on fashion Small Medium Entreprises (SMEs) in Indonesia utilizing strategies and efforts to develop value creations. It is generated by co-creation and collaboration strategy which are supported by market attractiveness and dynamic capabilities. The objectives of this study are to perform analysis on co-creation, collaboration strategy and value creations of SMEs in fashion industry. The research method is descriptive and explanatory survey. The sample size are thirty one SMEs in Bandung and Partial Least Square (PLS) technique was used to test the hypothesis model. The unique findings is co-creation and collaboration strategy have influence on value creations. Market attractiveness or potential profitability be a major input in formulating and implementing both strategies. The phenomena depicted that optimizing market attractiveness and dynamic input capabilities can help SMEs formulate and implement co-creation and collaboration strategy more effectively to create value for customers (value creations). This research gave theoritical recommendation for fashion industry to enhance their value creations process and to develop co-creation and collaborations strategy. &nbsp