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Validating knowledge and technology effects to operative sustainable competitive advantage

Takala J., Koskinen J., Liu Y., Tas M. S., Muhos M.

Management and Production Engineering Review

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2013

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Vol. 4, No. 3

45--54

EN

Purpose: This paper aims to present a fresh idea on how to model and examine the level of sustainable competitive advantage (SCA) with and without knowledge and /technology (K/T) effects in a case company’s operation by taking the manufacturing strategy’s development directions and the efficiency of resource allocation among its attributes into consideration. Design/Methodology/approach: In this paper, questionnaires are filled by two different managerial groups, company’s management team (G1) and company’s global directors (G2). The analyses based on G1, G2 and G1-G2 (mixed results) are performed and examined as well as the effect of knowledge and /technology rankings to observe the differences on how they effect on company’s operations strategy and what kind of strategy type that decision makers might follow. Besides, the effects of knowledge/technology rankings on SCA risk levels are examined on different case companies to perceive the similarities and differences with our case company. In this case study, the objectives are achieved based on several methodologies: manufacturing strategy index (MSI) [1] and sense and respond (S&R) methodology [2]. Findings: The achieved results through the model are found to be promising corresponding to the feedback from the respondents. Research limitations/implications: The model is applied only in a big sized B2B global company that produces power electronics products. Therefore, further tests need to be applied to the model in case of multiple companies from different sizes and areas to figure out the best formula in case of validation of strategic direction (MAPE, RSME or MAD). Practical implications: As a result of its wide applicability and its ease in arrangement the model has an enormous potential for strategic decision-making process and strategic analysis. Originality/Value:The model can provide a more dependable possibility of sustainable improvement to the corporate operational excellence and strategy.

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Using sustainable competitive advantages to measure technological opportunities

Takala J., Muhos M., Tilabi S., Tas M. S., Yan B.

Management and Production Engineering Review

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2013

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Vol. 4, No. 3

55--64

EN

The goal of this paper is to help small and medium size enterprises (SMEs) to find operative competitive advantage. This paper introduces a new method which applies critical factor analysis, risk and opportunities analysis to measure and propose resource allocation for companies in couple of next years. this research shows Knowledge/Technology (K/T) Calculation effect on (Balanced) Critical Factor Index (CFIs) depending on the proportions allocated among the different technological levels (Basic, Core or Spearhead) for each attribute separately. Moreover it helps firms to take balance in resource allocation for each attribute in changing environments on the basis of different level of technology. This paper presents the ’first in the world’ case study on operative sustainable competitive advantage and corresponding risk levels by taking into account technology and knowledge effects for 7 SME companies.

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SMEs' performance evaluation and optimization based on DEA and CFI

Shi Z., Takala J., Muhos M., Poikkimaki J., Chen Y.

Management and Production Engineering Review

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2013

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Vol. 4, No. 1

57-64

EN

It is a core content of enterprise performance research evaluating and comparing enterprise performance in dynamic environment. In allusion to this problem, a variety of enterprise performance assessment methods and indexes systems are proposed. Data envelopment analysis (DEA) is a kind of effective mathematical model which is used for comparing the performance among enterprises or different units inside an enterprise, based on the real-world data. Through comparing the performance, DEA can evaluate the enterprise performance from scale effectiveness and technological effectiveness, and then get the performance optimization goals. Critical Factor Index (CFI) is a new enterprise performance assessment method proposed in recent years. This method, based on the performance perception of business leaders or staffs, evaluates the enterprise performance in different dimensions, and then gets the optimization strategy of enterprise resource allocation to improve integrated enterprise performance. This paper has structured a new evaluation and optimization system for performance of small and medium-sized enterprises (SMEs), which combine properly the DEA and CFI method to evaluate and optimize the SMEs' performance comprehensively, and has confirm this system with data of 5 Finnish SMEs.