The innovation incubator,university business incubator and technology transfer strategy: The case of Thailand

This study reviews the role of the innovation incubator and university business incubator (UBI) in supporting the entrepreneurial development in Thailand. The university business incubator (UBI) is defined in this paper as an incubator set up by the university to provide office space, equipment, mentoring services as well as other administrative supports to assist the formation of new ventures). In particular, the paper compares the operation of the university business incubators (UBIs) and technology incubators to understand their technology transfer strategies. The analyses, based on the Triple Helix model, also include the government policies to support innovation commercialization in Thailand. The study examines case studies of leading university business incubators (UBIs) (Mahidol University, Chulalongkorn University and King Mongkut's University of Technology Thonburi) and science and technology incubators of the National Science and Technology Agency (NSTDA) and the National Innovation Agency (NIA). The results have shown that the incubation program is one of the major policy mechanisms to support innovation and suggested that UBIs should act as an intermediary between the spheres of university and industry to provide interactive linkages and promote effective utilization of university research. The empirical study provides insightful implications on the move towards the entrepreneurial university and the dynamics of the Triple Helix system in stimulating innovation development and diffusion.     

Contract negotiation and risk preferences in dual-channel supply chain coordination

This study employs profit-sharing contracts to coordinate dual-channel supply chains and examines the selection of profit-sharing parameters and the allocation of extra system profit gained from coordination. We characterise the Pareto-optimal contracts for the two- and three-stage dual-channel supply chains, by developing and maximising system utility function related to risk preferences and negotiating power. Under the optimal profit-sharing parameter in a two-stage supply chain, both members are reluctant to cooperate; however, in a three-stage supply chain, under the optimal two profit-sharing parameters selected by optimising the system utility function, the retailer is always reluctant to cooperate, but the distributor or the supplier may have incentives to deviate from cooperation. In this case, the distributor and the supplier will negotiate again as in a two-stage supply chain so that all three members can benefit from coordination with profit-sharing contracts. Besides acting independently, the distributor, in the process of contract negotiation, may choose to form an alliance with the upstream supplier or the downstream retailer, which means the relationship among the three members involving profit allocation after coordination is quite different from that for a two-stage supply chain and is not necessarily interest-contrary. In the contract negotiation, in any kind of scenario, risk aversion and negotiation power have a significant impact on the selection of optimal profit-sharing parameters and the allocation of extra system profit. One member’s risk aversion or its negotiation power may be advantageous to the other. Mathematical examples are illustrated to clarify the contract negotiation process.     

The Incubatees’ Perspective on Identifying Priority Enabling Factors for Technology Business Incubators

Abstract

Previous studies have identified enabling factors needed to support technology business incubatees which are usually small and medium enterprises. However, these studies were unable to draw conclusions about which enabling factor has the most impact and thus should receive the most attention. In the perspective of a developing country such as the Philippines where economic development is important, enabling factor identification is a crucial task as it provides inputs to decision-makers, policy-makers, and engineering managers in framing guidelines and directions for important activities such as resource allocation, strategic planning, prioritization of initiatives, and policy formulation. A case study was carried out at the University of the Philippines Technology Business Incubator (TBI), one of the established TBIs in the Philippines. Prioritization was performed using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Findings suggest that on-site business expertise, the suggested ideas on situational experiences (technology/ideas), and the confidential techniques or information that would assist the incubatees (know-how) are the most relevant enabling factors for incubatees’ success. In contrast, in-kind financial support, concise program milestones with clear policies and procedures, and expert organization emerge as the least important factors. Engineering managers are crucial in addressing these top enabling factors. These would help incubators and engineering managers formulate policies to improve their operations such as attracting and retaining the best management academics and practitioners to support their incubatees. Engineering managers can support incubatees in optimization studies and engineering experiments for the efficient and effective adoption of the incubatees’ technologies. Policy-makers must also consider incentivizing private institutions and successful entrepreneurs to be involved in the incubation programs.     

Acquisition of new technology information for maintenance and replacement policies

In this paper, we propose the first model that considers the option to acquire information on the profitability of a new technology that is not yet available on the market for asset maintenance and replacement decisions. We consider the uncertainty of future asset characteristics by incorporating information acquisition decisions into a non-stationary Markov decision process framework. Using this framework, we optimise asset maintenance and replacement decisions as well as the optimal timing of new technology adoption. Through mathematical analyses, the monotone properties and convexity of the value function and optimal policy are deduced. Deeper numerical analyses highlight the importance of considering the acquisition of information on future technology when formulating a maintenance and replacement policy for the asset. We also deduce a non-intuitive result: an increase in the arrival probability of new technology does not necessarily make the acquisition of additional information more attractive.     

Modelling and analysis of a business model to offer energy-saving technologies as a service

In this study, we present a stochastic model to analyse a business plan that is based on offering energy-saving technologies as a service. In this arrangement, the total differential cost of replacing an existing technology with a more efficient one is financed from the future energy savings that are shared between a service provider that installs the more efficient technology and its customer. The model we present captures improvements in energy efficiencies and costs of technologies with time, variation in energy consumption, uncertainty in energy prices and useful life of a technology, and revenue from carbon offsets. By using an analytical model, we analyse the feasibility of this business model using expected cost and also value-at-risk criteria. We show that when the service provider selects the contract parameters in a right way, the business plan brings financial benefits. The customer also benefits financially from reduction in energy usage and replacement costs, and also from additional revenue obtained through selling carbon offsets. Furthermore, since this business plan is based on increasing energy efficiency, the proposed approach decreases energy consumption, and therefore carbon dioxide emissions. As a result, using an analytical model, we show that offering energy-saving technologies as a service is a win–win–win situation for the service provider, its customer and for the environment.     

A new DEA common-weight multi-criteria decision-making approach for technology selection

This paper addresses an advanced manufacturing technology selection problem by proposing a new common-weight multi-criteria decision-making (MCDM) approach in the evaluation framework of data envelopment analysis (DEA). We improve existing technology selection models by giving a new mathematical formulation to simplify the calculation process and to ensure its use in more general situations with multiple inputs and multiple outputs. Further, an algorithm is provided to solve the proposed model based on mixed-integer linear programming and dichotomy. Compared with previous approaches for technology selection, our approach brings new contributions. First, it guarantees that only one decision-making unit (DMU) (referring to a technology) can be evaluated as efficient and selected as the best performer while maximising the minimum efficiency among all the DMUs. Second, the number of mixed-integer linear programs to solve is independent of the number of candidates. In addition, it guarantees the uniqueness of the final optimal set of common weights. Two benchmark instances are used to compare the proposed approach with existing ones. A computational experiment with randomly generated instances is further proceeded to show that the proposed approach is more suitable for situations with large datasets.     

A supply chain transparency and sustainability technology appraisal model for blockchain technology

Blockchain technology is a technology that can effectively support supply chain transparency. An important initial managerial activity is for organisations in supply chains to evaluate and select the most suitable blockchain technology. However, uncertainty and emphasis on sustainable transparency has made this appraisal more complex. This paper: (1) introduces blockchain technology performance measures incorporating various sustainable supply chain transparency and technical attributes; and (2) introduces a new hybrid group decision method, integrated hesitant fuzzy set and regret theory, for blockchain technology evaluation and selection. This method emphasises decision maker psychological characteristics and variation in decision maker opinions. An illustrative application and sensitivity analysis is introduced to aid supply chain managers and researchers understand the blockchain technology selection decision. Methodological and managerial implications associated with the decision tool and application are introduced. This research sets the foundation for significant future research in blockchain technologies evaluation in a supply chain environment.     

Optimal compensation rules for integrated services

Research on service compensation is rare. In this article we examine different compensation rules for integrated services (IS) which are produced jointly by a service provider and his client. Examples are consulting, advertising or management training. We distinguish three different compensation rules and compare them with joint profit maximization where both, service provider and client act as one organizational unit. The compensation rules are (1) the input based compensation (IBC) characterized by a compensation that is based on work hours or work days, (2) the sales based compensation (SBC) with the compensation based on client’s sales and (3) the profit based compensation (PBC) with compensation based on client’s profits. We can show that under reasonable, realistic conditions the IBC (surprisingly) leads to better results for the service provider and for the client as compared to the PBC and the SBC.     

Balancing desirable but conflicting objectives in the newsvendor problem

In this paper we study the problem of balancing two desirable but conflicting objectives in the newsvendor model. The standard objective in the newsvendor model is the expected profit maximization. Another objective (known as the "satisficing"--or, "aspiration-level"--objective) that has been studied in the literature is the probability of exceeding a prespecified and fixed target profit level. Since it may not always be obvious what the fixed target profit level should be, we introduce a more flexible satisficing objective where the target does not have to be prespecified. Our satisficing/aspiration-level objective is defined as the probability of exceeding the expected profit and it is a "moving" target that is a function of the order quantity. We provide a discussion of the properties of the newly introduced probability maximization objective. As a departure from previous work where the individual objectives were considered in isolation, in this paper we develop a model that unifies and integrates the two objectives. We use a scalarization method to combine the standard objective of expected profit maximization with the new objective of maximizing the probability of exceeding the moving target. A decision framework is developed within compromise programming that involves minimizing a generalized distance function measuring the "distance" from an ideal point to the efficient frontier. Several examples illustrate the results.     

Design technology transfer

Design technology and its transfer are defined and their significance stated. The history of design technology (DT) is outlined, noting a recent change in nature. Factors influencing the development and spread of DT are investigated, first by the use of pieces of available research results, and then through analysis of 12 case summaries assembled for the purpose. Hypotheses are advanced regarding the i influence of large ‘front-runner’ companies and, particularly, of companies in the information technology fields. Suggestions are offered to university departments wiching to participate more fully in design technology transfer.     

Pricing and production decisions in a closed-loop supply chain considering strategic consumers and technology licensing

This paper considers a closed-loop supply chain consisting of a manufacturer and a third party in which the manufacturer licenses the third party to undertake remanufacturing activities in the presence of strategic consumers. We analyse the impacts of strategic consumer behaviour and the third-party remanufacturing cost on three kinds of remanufacturing scenarios, namely no-remanufacturing, partial-remanufacturing and full-remanufacturing. We adopt a Stackelberg game to obtain the equilibrium strategies of each remanufacturing model and show that the demand of new products decreases and the demand of remanufactured products increases as consumers become more strategic. Considering the manufacturer’s profit decrease due to strategic consumer behaviour, the manufacturer suffers a smaller profit loss when he licenses the third party to remanufacture because he can charge a higher licensing fee from the third party to share remanufacturing revenues. Moreover, the manufacturer prefers the third-party remanufacturing mode rather than the manufacturer–remanufacturing mode if the third-party remanufacturing cost is relatively low and remanufacturing can always bring a profit increase to both the manufacturer and the third party.     

A two-step optimization approach for technology selection

An efficient optimization approach for the technology selection problem is described. Technology selection is a crucial step in the aircraft design process, especially when the performance and econo-mic requirements are not fulfilled for any combination of the configuration design variables. In such a case, the designer must search efficiently within a set of technology options for the optimal combination that achieves the required improvements. When the set of available technologies is large, as is usually the case, a difficult combinatorial optimization problem ensues, resulting in significant time and computational expense. The objective of the new approach is to reduce the computational cost of technology selection by decomposing the process into two smaller sub-problems. The new approach attempts to exploit the structure of the technology compatibility matrix to improve the efficiency of the technology selection process. Results from an application problem are presented and valuable insights and observations are discussed.     

云制造模式下基于多目标非合作博弈的服务租赁定价策略

传统的制造企业通过销售产品和一定的售后服务获得利润,而在云制造模式下,关注产品质量、延长使用寿命,将产品作为服务租赁给客户成为一种新的盈利模式。本文将云服务平台中的服务提供方和服务需求方作为博弈双方,从供需Stackelberg博弈角度,结合大数据分析预测产品剩余使用寿命(remaining useful life, RUL),建立了云制造服务平台服务租赁的双层规划模型。双层规划问题是一类具有主从递阶结构的复杂决策问题,具有NP-hard性。本文使用带精英策略的非支配排序遗传算法(nodominated sorting genetic algorithm II, NSGA-II,)对模型进行求解,并使用某刀具厂案例验证模型实用性和有效性。     

A technology selection framework for integrating manufacturing within a supply chain

This paper describes a structured analytical approach for selecting a manufacturing technology. A framework consisting of six integrated steps is proposed by considering the growing importance of supply chains in manufacturing organisations. The framework makes use of the analytical hierarchy process (AHP) approach combined with strategic assessment model (SAM) to evaluate and select the technologies appropriate for providing overall competitive advantage. The framework is intended to assist industrial managers in promoting manufacturing and supply chain collaboration and co-ordination by including intra-organisational perspective in their organisational technology selection decision making process.     

Economic Evaluation Model for International Standardization of Technology

This paper proposes an economic evaluation model for international standardization to support the decision-making process of technology development and standardization. We make use of a cost of ownership (COO) model for analyzing both expected-benefit and cost-of-technology development and standardization. Then, we apply the proposed model to a case of radio frequency identification (RFID) technology by establishing four potential scenarios. From the scenario analysis, the expected profit of the international standardization is evaluated for each scenario. We also perform sensitivity analysis to consider the effect of various parameter settings. This paper is expected to lead companies in the choice of the best strategy of technology development and standardization that would bring maximum profit.      

Improving the performance of retail stores subject to execution errors: coordination versus RFID technology

This paper analyzes a Newsvendor type inventory model in which a manufacturer sells a single product to a retailer store whose inventory is subject to errors stemming from execution problems. Hence, within the store, all of the products are not available on shelf for sales either because the replenishment of the shelf from the backroom is subject to execution errors that mainly result in products lost in the backroom or products misplaced on the other shelves of the store. We compare two situations: in the first situation, the two supply chain actors are aware of errors and optimize their ordering decisions by taking into account this issue. The second situation deals with the case where an advanced automatic identification system such as the Radio Frequency Identification technology is deployed in order to eliminate errors. Each situation is developed for three scenarios: in the centralized scenario, we consider a single decision-maker who is concerned with maximizing the entire supply chain’s profit; in the decentralized uncoordinated scenario, the retailer and the manufacturer act as different parties and do not cooperate. The third scenario is the decentralized coordinated scenario where we give conditions for coordinating the channel by designing a buyback contract. The authors would like to thank the editor, Prof. Dr. Hans-Otto Guenther, and two anonymous referees for their constructive comments to improve this article.     

A-E方法的多目标车间排产方案精选决策

分析车间排产方案决策阶段企业各部门利益关系,构建基于层次分析和熵理论(A-E)及欧氏范数的多目标车间排产方案决策模型.具体利用AHP法建立车间排产方案层次化的决策体系,采用层次分析法和熵理论(A-E)方法确定各决策因素的权重.在车间排产决策中,利用欧氏范数来描述备选排产方案与理想方案的距离大小作为精选的依据.并结合实例进行数值演算和验证,计算表明该模型能根据生产实际数据帮助决策者快速的从多个车间排产方案中精选,得到令各部门最满意的唯一方案.     

Economic determination of specification levels and allocation priorities of semiconductor products

We construct and analyze an economically efficient way of pricing and allocating semiconductor chips of which production technology is characterized by persistent quality variations and of which production capacity is exceeded by potential demand. In our model, specification levels and allocation priorities of competing orders from customers are systematically determined for a single profit maximizing producer. In the proposed scheme, the producer offers a 'product line' of priority classes under an allocation rule that always supplies higher priority classes with higher spec, level chips. This product line design and allocation rule enable us to cast the producer's profit maximization problem as a nonlinear programming formulation. Also, we investigate the optimality of the proposed allocation rule and derive conditions under which the profitability of downgrading is determined.     

DEA cross-efficiency evaluation based on satisfaction degree: an application to technology selection

Data envelopment analysis (DEA) has been extended to cross-efficiency evaluation to provide better discrimination and ranking of decision-making units (DMUs). However, the non-uniqueness of optimal weights in the traditional DEA models (CCR and BCC models) has reduced the usefulness of the DEA cross-efficiency evaluation method. To solve this problem, we introduce the concept of the satisfaction degree of a DMU towards a set of optimal weights for another DMU. Then, a new DEA cross-efficiency evaluation approach, which contains a maxmin model and two algorithms, is proposed based on the satisfaction degrees of the DMUs. Our maxmin model and algorithm 1 can obtain for each DMU an optimal set of weights that maximises the least satisfaction degrees among all the other DMUs. Further, our algorithm 2 can then be used to guarantee the uniqueness of the optimal weights for each DMU. Finally, our approach is applied to a real-world case study of technology selection.     

基于人工神经网络-粒子群算法激光烧蚀制备PDPhSM基纳米复合薄膜的工艺优化

为有效缩短脉冲激光烧蚀制备有机硅聚合物聚二苯基硅亚甲基硅烷(Polydiphenylsilylenemethyle,PDPhSM)基纳米复合薄膜工艺中繁琐的试验过程,本文将用径向基函数(Radial BasisFunction,RBF)人工神经网络对聚合物PDPhSM基纳米复合薄膜的制备工艺与聚合效率之间的关系进行建模;讨论了激光能量密度、环境压强、靶衬距离、沉积时间和聚合效率之间的关系.在此基础上,采用粒子群(Particle Swarm Optimiza-tion,PSO)算法对其进行工艺优化,200代以后,粒子素质明显提高,k值趋近于0,群体达到了最优,工艺参数的优化结果较为满意.从而为薄膜材料工艺优化研究探索了一条崭新的途径.