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Current industrial scenario is largely dependent on cloud computing paradigms. On-demand services provided by cloud data centre are paid as per use. Hence, it is very important to make use of the allocated resources to the maximum. The resource utilization is highly dependent on the allocation of resources to the incoming request. The allocation of requests is done with respect to the physical machines present in the datacenter. While allocating the tasks to these physical machines, it needs to be allocated in such a way that no physical machine is underutilized or over loaded. To make sure of this, optimal load balancing is very important.

The paper proposes an algorithm which makes use of the fitness functions and duopoly game theory to allocate the tasks to the physical machines which can handle the resource requirement of the incoming tasks. The major focus of the proposed work is to optimize the load balancing in a datacenter. When optimization happens, none of the physical machine is neither overloaded nor under-utilized, hence resulting in efficient utilization of the resources.

The performance of the proposed algorithm is compared with different existing load balancing algorithms such as round-robin load (RR) ant colony optimization (ACO), artificial bee colony (ABC) with respect to the selected parameters response time, virtual machine migrations, host shut down and energy consumption. All the four parameters gave a positive result when the algorithm is simulated.

The contribution of this paper is towards the domain of cloud load balancing. The paper is proposing a novel approach to optimize the cloud load balancing process. The results obtained show that response time, virtual machine migrations, host shut down and energy consumption are reduced in comparison to few of the existing algorithms selected for the study. The proposed algorithm based on the duopoly function and fitness function brings in an optimized performance compared to the four algorithms analysed.

How do cultural organizations handle the competing demands of isomorphism and differentiation? Strategic balance theory is a promising point of departure. Proponents argue that while isomorphism contributes to legitimacy, differentiation minimizes competition through innovation or niche control. However, most research has focused on successful cases of optimal performance in core or world cities. I introduce data from three seasons (250+ hours) of ethnographic research on fashion weeks in both a core city and semi-peripheral city. I find that geography acts as a structural barrier to competition: while semi-peripheral producers pursue some standards of fashion capitals in world cities, they cannot compete on the basis of style. Rather than optimizing through strategic balance, cultural organizations embrace a double edge of legitimation. Their sub-optimal vision of organizational survival cultivates legitimacy from available but symbolically polluting sources. Imperfect imitation is suggested instead as a viable legitimation strategy. I call for more attention to semi-peripheral geography and imperfect imitation in culture industry research.

The purpose of this paper is to explore the system requirements model. According to the concept of loss costs of Type I and Type II errors, it can define the optimal decision line, and reduce overall loss costs. Moreover, it can decrease the probability of Type I and Type II error by the systems thinking, and it can effectively reduce overall loss costs.

The paper proposed a system demand model and constructed a decision‐making system thinking model as well as a decision‐making performance management model using the principle of system demand. Types of decision‐making errors were analyzed to set judgments on the error risk and establish a model of improvement evaluation key factors, in order to reduce decision‐making error risk and enhance decision quality. It also constructed the improved decision‐making to assess the key factors, to reduce the risk of making errors in order to improve the quality of decision‐making.

Optimistic decision‐makers (risk takers) tend to make Type II errors, whereas pessimistic decision makers (conservatives) tend to make Type I errors. Financial depressions are the time for optimistic decision makers (risk takers) and boom periods are the time for pessimistic decision makers (conservatives).

The concept of the loss cost of two decision‐making errors and related cost function models were proposed. Decision makers could make decisions with a more stable model, taking into consideration false alarms and the cost function of errors in order to determine the position of the decision‐making line. It could effectively reduce decision‐making error costs and increase the precision of decision‐making.

Dynamic capabilities and organizational ambidexterity are closely related concepts. Unfortunately, there is still a lack of understanding about the relation between the two. This paper aims to offer a theoretical explanation of the relationship between dynamic capabilities, organizational ambidexterity and firm competitive advantage. The authors find that organizational ambidexterity may be considered as a mediator in the relationship between dynamic capabilities and firm competitive advantage. Therefore, this paper contributes theoretically to the authors’ understanding of the relationship between organizational ambidexterity and dynamic capabilities with regard to firm competitive advantage.

In this conceptual paper, the review of research literature on dynamic capabilities and organizational ambidexterity is presented. Theoretical analysis is followed by theoretical prepositions that should be subsequently tested empirically.

By considering dynamic capabilities and organizational ambidexterity related to competitive advantage, this paper provides a new perspective on concepts’ relationship. The theoretical findings described in this paper suggest that organizational ambidexterity plays a mediating role in the relationship between dynamic capabilities and firm competitive advantage.

Further research are required to develop organizational ambidexterity and dynamic capabilities theories, focusing more on the relation to competitive advantage. Additional testing is necessary to empirically validate the propositions given in this paper.

Based on theoretical findings, this paper clarifies the relationship between dynamic capabilities and organizational ambidexterity concepts. Theoretical findings described in this paper also determine the guidelines for further theoretical and empirical research within the fields.

Balancing interfirm relationships is important for firms’ long-term superior performance. However, prior studies mainly focus on interfirm competition or interfirm cooperation separately, ignoring the balance of interfirm relationships. To bridge this gap in knowledge, this study aims to develop a framework to evaluate the balance of interfirm competition and interfirm cooperation and propose strategies to optimize a firm’s interfirm relationships.

After an in-depth literature review, a framework was developed for evaluating and optimizing the interfirm relationships. Taking the high-speed railway industry as an example, the proposed framework was implemented.

The results of the case confirm that the balancing of interfirm relationships can lead to more superior firm performance. Also, rather than mutual suppression, the interfirm competition and interfirm cooperation present a roughly positive relationship.

This study would contribute to the existing knowledge body by developing a framework for balancing interfirm relationships. Also, this study can aid practitioners in evaluating and optimizing their interfirm relationship structures.

The purpose of this paper is to suggest that in the arena of human capital, risk-mitigation may overshadow risk-optimized decisions, and show how a more balanced approach can be achieved by understanding and applying frameworks from behavioral decision theory, as well as framing human capital risk using tools and frameworks that have a long history in other management arenas, such as finance.

Review risk-optimization frameworks in human resource and general management, distill key connections, suggest ways to enhance risk optimization for human capital, and offer suggestions for future research and practice.

For human capital, risk-mitigation may overshadow risk-optimization, a balanced approach can be achieved by applying behavioral decision theory and by using frameworks from other management arenas, such as finance.

Organizations must acknowledge and skillfully manage the connections between human capital and competitive strategy in this emerging arena of human capital risk, or they will miss key strategic opportunities.

Attention to human capital risk has largely emphasized minimizing or controlling unwanted outcomes, but the paper proposes that risk-optimization requires balanced attention to risk-taking as well.

Design, balancing, and sequencing are the key issues associated with assembly lines (ALs). The purpose of this paper is to identify AL design issues and to develop an integrated methodology for mixed‐model assembly line balancing (MMALB) and sequencing. Primarily, mixed‐model lines are utilized for high‐variety, low‐volume job shop or batch production. Variation of a generic product is important for the manufacturers as the demand is mostly customer driven in the present global market.

Different AL design norms, performance indexes, and AL workstation indexes have been identified in the initial stage of this work. As the paper progresses, it has focused towards an integrated approach for MMALB and sequencing addressed for small‐ and medium‐scale assembly plants. A small‐scale practical problem has been justified with this integrated methodology implemented by MATLAB.

ALs execution in the production floor require many important factors to be considered. Different line orientations, production approaches, line characteristics, performance and workstation indexes, problem definitions, balancing and product sequencing in accordance with the objective functions are needed to be taken into account by the line designer.

This paper has highlighted the important AL design characteristics and also provided an integrated approach for balancing mixed‐model assembly lines (MMALs) combined with sequencing heuristic. The findings of this paper can be helpful for the designers while designing an AL. The integrated approach for balancing and sequencing of MMALs can be used as a functional tool for assembly‐based contemporary industries.

Service providers increasingly use conversational agents (CAs), such as chatbots, to effectively communicate with customers while managing interaction costs and providing round-the-clock customer service. Yet, the adoption and implementation of such agents in service contexts remains a hit-and-miss, and firms often struggle to balance their CAs implementation complexities and costs with relation to their service objectives, technology design and customer experiences. The purpose of this paper is to provide guidance on optimizing CA design, therefore, the authors develop a conceptual framework, TRISEC, that integrates service logic, technology design and customer experience to examine the implementation of CA solutions in search, experience and credence (SEC) contexts.

The paper draws on service marketing and communications research, combining the service context classification scheme of search, experience and credence and the technology infused service marketing triangle foci (service, technology and customer) in its conceptual development.

The authors find that an opportunity exists in recognizing the importance of context when designing CAs and aiming to achieve a balance between service objectives, technology design and customer experiences.

This study contributes to service management and communications research literature by providing interactive service marketing researchers with the highly generalizable TRISEC framework to aid in optimizing CA design and implementation in interactive customer communication technologies. Furthermore, the study provides an array of future research avenues. From a practical perspective, this study aims at providing managers with a means to optimize CA technology design while maintaining a balance between customer centricity and implementation complexity and costs in different service contexts.

The main purpose of this paper is to develop a study of the determination of the most appropriate execution steps, necessary for the construction of modelling, simulation and optimization for the specific area of slaughter line balancing. And through the developed model to demonstrate the application of simulation to increase productivity in a large-size swine slaughterhouse, focusing on operator stations balancing. The built model may be applied to support the management of the plant, allowing to evaluate and decide the optimized scenario that meets current needs considering operational cost, production demand and productivity.

For the research development, the selected software supports the characteristics of the evaluated process, in this case, a discreet simulation with stochastics variables. The studied plant was modelled door by door, from the swine reception until the packaging area. The research methodology was based on lean manufacturing (LM) principles, particularly in workstations balancing, by optimizing the idle time of the operators, comparing with the cycle time of each task, in the evaluated workstations.

The achieved result with the modelling and simulation was the increase of 11.89% in plant productivity through manpower optimization. The study indicates that the simulation applied with LM concepts as operative stations balancing and value stream map can be a very useful tool to support decision-making for productivity improvement.

This study approaches how modelling and simulation can support decision-making to implement improvements associated to workforce balancing optimization, especially in the studied area (agribusiness, animal slaughter). The studied process presents great variability associated with the processing time of each phase, making the analysis and modelling more complex. The number of workstations involved, with more than 800 employees, is an important point in the research, considering that cases with higher values than the case presented were not identified in literature.

The product family assembly line (PFAL) is a mixed model-assembly line, which is widely used in mass customization and intelligent manufacturing. The purpose of this paper is to study the problem of PFAL, a flexible (evolution) planning method to respond to product evolution for PFAL, to focus on product data analysis and evolution planning method.

The evolution balancing model for PFAL is established and an improved NSGA_II (INSGA_II) is proposed. From the perspective of data analysis, dynamic characteristics of PFAL are researched and analyzed. Especially the tasks, which stability is considered, can be divided into a platform and individual task. In INSGA_II algorithm, a new density selection and a decoding method based on sorting algorithms are proposed to compensate for the lack of traditional algorithms.

The effectiveness and feasibility of the method are validated by an example of PFAL evolution planning for a family of similar mechanical products. The optimized efficiency is significantly improved using INSGA_II proposed in this paper and the evolution planning model proposed has a stronger ability to respond to product evolution, which maximizes business performance over an effective period of time.

The assembly line designers and managers in discrete manufacturing companies can obtain an optimal solution for PFAL planning through the evolution planning model and INSGA-II proposed in this paper. Then, this planning model and optimization method have been successfully applied in the production of small wheel loaders.