Search results

The purpose of this paper is to clarify recent research on knowledge development in Facility Management (FM); identify types of knowledge and its degree of importance in the FM field within the Malaysian environment; and how does it benefit Hospitality Management (HM) in terms of managerial competency.

The nature of this study is quantitative. Data were gathered through questionnaires distributed to various practitioners in the FM field in the private sector and government sector in Malaysia.

The analysis results support that all types of knowledge, which was considered important, are required to develop a conceptual model of training syllabus for an intensive training program. The analysis results will be discussed in the context of hospitality management. In addition, a decision-making tree model was created to facilitate the training program in the future with the aim of developing a competency model.

Most of the participants have experience with the FM field. Future research is recommended to include the conceptual model of training syllabus in analysis information relating to managers directly involved with the orientation of HM.

This paper presents a quantitative survey regarding the importance of knowledge in the FM industry in Malaysia and generally discusses the link between FM and Hospitality managerial competency. Further, this research delivers useful information for FM and HM managers who intend to further develop the practical training program based on the proposed decision-making tree model.

The emergence of the fast fashion trend has exerted a great pressure on fashion designers who are urged to consider customers’ preferences in their designs and develop new products in an efficient manner. The purpose of this paper is to develop a fuzzy association rule mining (FARM) approach for improving the efficiency and effectiveness of new product development (NPD) in fast fashion.

The FARM identifies the hidden relationships between product styles and customer preferences. The knowledge discovered help the fashion industry design new products which are not only fashionable, but are also saleable in the market.

To evaluate the proposed approach, a case study is conducted in a Hong Kong-based fashion company in which a real-set of data are tested to generate fuzzy association rules. The results reveal that the FARM approach can provide knowledge support to the fashion industry during NPD, shorten the NPD cycle time, and increase customer satisfaction.

Compared with traditional association rule mining, the proposed FARM approach takes the fuzziness of data into consideration and the knowledge represented in the fuzzy rules is in a more human-understandable structure. It captures the voice of the customer into fashion product development and provides a specific solution to deal with the challenges brought by fast fashion. In addition, it helps increase the innovation and technological capability of the fashion industry.

This paper applies the knowledge-based genetic algorithm to solve the optimization problem in complex products technological processes.

The knowledge-based genetic algorithm (KGA) is defined as a hybrid genetic algorithm (GA) which combined the GA model with the knowledge model. The GA model searches the feasible space of optimization problem based on the “neighborhood search” mechanism. The knowledge model discovers some knowledge from the previous optimization process, and applies the obtained knowledge to guide the subsequent optimization process.

The experimental results suggest that the proposed KGA is feasible and available. The effective integration of GA model and knowledge model has greatly improved the optimization performance of KGA.

The technological innovation of complex products is one of effective approaches to establish the core competitiveness in future. For this reason, the KGA is proposed to the technological processes optimization of complex products.

The main purpose of the paper is to assess and suggest the ways and means to enhance a collaborative knowledge sharing culture in academic institutions, with special reference to information technology (IT)‐related education in the Management Faculty of the University of Pune.

The research is descriptive and empirical in nature because the primary data were collected using the survey method through fact finding techniques such as questionnaire and interview. The main purpose of this research is to obtain information concerning the current status of the phenomena to describe “what exists” with respect to variables or conditions in a situation.

The sustainability of any industry is closely linked to the manpower talent made available by the academic institutions. Therefore in order to service the needs of the industry in tune with rapidly changing trends, academic institutions have to implement innovative learning systems and be able to match up to the expectations of the industry for knowledge support. Collaborative knowledge sharing links the learning and knowledge processes to enhance organizational learning. The knowledge grows more with communication, sharing of ideas and transfer of knowledge through face‐to‐face communication, discussions, faculty development programs, industry‐institute interactions. Academic institutions should align their human resource strategies, practices and processes in such a way that collaborative knowledge sharing becomes a part of the work culture and overcome the barriers to knowledge sharing. There is need to develop systems that can recognize and reward the efforts of employees who share their knowledge. This can empower collaborative knowledge sharing culture in an academic institute.

In the same context as the practical implications of the paper, it is also appropriate and important to study further how, and to what extent collaborative knowledge improves the performance of the academic institutes. Also, the impact of collaborative knowledge sharing on the quality of higher education.

The recommendations in this paper focus on factors influencing collaborative knowledge sharing culture and also the practices of collaborative knowledge sharing to enhance organizational learning in an academic institute.

This paper contributes original empirical data on the collaborative knowledge sharing strategy to enhance organizational learning.

The purpose of this paper is to examine the problem of rate allocation (RA) in computer networks in cases when some parameters are unknown or their values are imprecise.

The application of uncertain variables for the RA problems in computer networks in the presence of uncertainty is proposed.

Decision‐making problem formulations for RA in computer networks with unknown parameters of the utility functions and bandwidths based on the network utility maximization concept are given. Solution algorithms for all these problems are proposed.

It is assumed that an expert can describe possible values of unknown network parameters in the form of a certainty distribution. Then, the formalism of uncertain variables is applied and the knowledge of an expert is modelled with certainty distributions.

The RA algorithms obtained can be useful for designing and planning computer networks.

The new approach to the RA problem in computer networks in the presence of uncertainty, in cases when the probabilistic approach cannot be applied, is proposed and discussed.

The purpose of this paper is to understand how Design for Additive manufacturing Knowledge has been developing and its significance to both academia and industry.

In this paper, the authors use a bibliometric approach to analyse publications from January 2010 to December 2020 to explore the subject areas, publication outlets, most active authors, geographical distribution of scholarly outputs, collaboration and co-citations at both institutional and geographical levels and outcomes from keywords analysis.

The findings reveal that most knowledge has been developed in DfAM methods, rules and guidelines. This may suggest that designers are trying to learn new ways of harnessing the freedom offered by AM. Furthermore, more knowledge is needed to understand how to tackle the inherent limitations of AM processes. Moreover, DfAM knowledge has thus far been developed mostly by authors in a small number of institutional and geographical clusters, potentially limiting diverse perspectives and synergies from international collaboration which are essential for global knowledge development, for improvement of the quality of DfAM research and for its wider dissemination.

A concise structure of DfAM knowledge areas upon which the bibliometric analysis was conducted has been developed. Furthermore, areas where research is concentrated and those that require further knowledge development are revealed.

The purpose of this paper is to solve the problem of low efficiency on knowledge resources allocation in the strategic emerging industry (SEI), an incentive model of technology innovation based on knowledge ecological coupling is designed.

First, a principal–agent model of knowledge inputs and a knowledge ecological coupling model based on an improved Lotka–Volterra model are constructed. In addition, a numerical example about Chongqing Yongchuan industrial park, the emulation analysis and the associated discussions are conducted to analyze the equilibriums of principal–agent in different knowledge inputs. Further, the paper analyzes the evolutionary equilibrium in knowledge ecological coupling and reveals the dual adjustments of the node organization on knowledge inputs.

Thus, this paper shows that by establishing the relationships of knowledge ecological coupling based on “mutualism and commensalism,” node organization raises the level of knowledge inputs; an incentive mode of “knowledge ecological coupling relationship + technology innovation chain” is conductive to substantially improving the efficiency of knowledge resource allocation, and to stimulate the vitality of node organization for technology innovation in the strategic emerging industry (SEI).

This paper contributes to the extant researches in two ways. First, this paper reveals the dual adjustments of the node organizations in inputting knowledge, which broadens the vision and borders of the researches on traditional knowledge management. The methods of the traditional principal–agent model and the knowledge input/output profit model are also expanded. Second, this paper verifies that applying the mode of “knowledge ecological coupling relationship + technology innovation chain” in practice is conducive to enhancing the efficiency of the cross-organizational knowledge allocation in the strategic emerging industry (SEI).

Knowledge input development and innovation implementation are new features of industrial technology innovation. The purpose of this study is to find the process of coordination and ecological spiral in the ambidextrous innovation of industrial technology.

To design the model of industrial technology ambidextrous innovation based on knowledge ecology spiral, an input-output model of knowledge for ambidextrous innovation and a spiral model of knowledge ecology were constructed based on an improved Lotka-Volterra model. Then, the equilibriums in different knowledge inputs and the spiral evolution of knowledge ecology were analyzed. Finally, the ambidextrous coordination mechanism of the core organization was revealed.

By coordinating the knowledge inputs and the knowledge ecology spiral, enterprises extend the R&D investments in the innovation chain, which will facilitate the knowledge inputs of the exploitative and exploratory innovation. Implementing the ambidextrous coordination in the technology innovation chain and the knowledge ecology chain has the advantage of promoting knowledge inputs, mobility and ecological spiral. Meanwhile, it can achieve the “multi-source, integration and coordination” development of industrial technology innovation.

The two-element innovative knowledge input coordination model and the knowledge ecological spiral model based on the improved Lotka-Volterra model are constructed, which extends the modeling way of the traditional knowledge input-output profit model. It is expected to reduce the amount of knowledge input of a single member and provide theoretical reference for improving the efficiency of knowledge input by constructing the inter-dependent regenerative and inter-generative knowledge interaction.

Israel, characterized by various knowledge-intensive entrepreneurial firms, provides an interesting case study for examining sector-based differences and “small country” regional patterns. This chapter has a dual goal of exploring sector and regional differences of knowledge-intensive firms in Israel. The first goal is to depict similarities and differences between firms in three knowledge-intensive sectors: Life Sciences, information technology, and Cleantech. The second goal questions whether the geographical distribution of these firms across regions is associated with different levels of knowledge concentration and organizational homogeneity. Regional and sector-based differences were measured by firm-level network structures, funding patterns, and innovation proxies. One way analysis of variance tests were conducted for attaining these research goals. The main findings show that while most regions exhibit similar patterns of firm and network characteristics, many differences exist on the sector level that are associated with sector-specific attributes. These findings support the notion of a “small country inter-regional homogeneity effect.”

This paper aims to discuss the methodology of mainstream Islamic economics and also gives an alternative approach which is yet not very much taught in the different academic institutions, i.e. Tawhidi methodology. From the curriculum of the different academic institutions and also from the literature, it is observed that mainstream Islamic economics is the imitation of the conventional economics and mainly neoclassical economics. Maqasid-i-Shari’ah is not matching with the Tawhidi one.

It is based on the self-observations of the authors where they taught during their academic career.

This study found that the mainstream Islamic economics could not be able to solve the local and global issues because it is the replica of the conventional economics only there are some injunctions of Shari’ah.

This study gives the guideline to the student of Islamic economics that how they will be able to understand the methodology of Islamic economics and finance.

It provides the guidance to the academicians and policymakers, especially those belonging to the Muslim countries.

It also provides the glimpses to the social scientist about the solutions of the social and economic issues at the local and global levels.

It is an original effort.