Hakyeon Lee

Benchmarking of service quality with data envelopment analysis

This paper proposes a data envelopment analysis (DEA) approach to measurement and benchmarking of service quality. Dealing with measurement of overall service quality of multiple units with SERVPERF as multiple-criteria decision-making (MCDM), the proposed approach utilizes DEA, in particular, the pure output model without inputs. The five dimensions of SERVPERF are considered as outputs of the DEA model. A case study of auto repair services is provided for the purpose of illustration. The current practice of benchmarking of service quality with SERVQUAL/SERVPERF is limited in that there is little guidance to whom to benchmark and to what degree service quality should be improved. This study contributes to the field of service quality benchmarking by overcoming the above limitations, taking advantage of DEAs capability to handle MCDM problems and provide benchmarking guidelines.

Identifying core technologies based on technological cross-impacts: An association rule mining (ARM) and analytic network process (ANP) approach

This study proposes a new approach to identifying core technologies from a perspective of technological cross-impacts based on patent co-classification information with consideration of the overall interrelationships among technologies. The proposed approach is comprised of two methods: association rule mining (ARM) and the analytic network process (ANP). Firstly association rule mining (ARM) is employed to calculate the technological cross-impact indexes. Since the confidence measure in ARM is defined as a conditional probability between two technologies, it is adopted as an index for evaluating technological cross-impacts. The technological cross-impact matrix is then constructed with all calculated cross-impact indexes. Secondly, the ANP, which is a generalization of the analytic hierarchy process (AHP), is conducted to produce priorities of technologies with consideration of their direct and indirect impacts. The proposed approach can be utilized for technology monitoring for both technology planning of firms and innovation policy making of governments. A case of telecommunication technology is presented to illustrate the proposed approach.

Identifying the structure of knowledge networks in the US mobile ecosystems: patent citation analysis

ABSTRACT With the emergence of smartphones, the paradigm of the mobile ecosystem has changed rapidly. In particular, global mobile firms focus on technological competition when jostling for market position in recognition of the strategic need to secure a strong mobile platform. In this paper, we analyse the network structure of technological knowledge flows in mobile ecosystems using US patent citation information. We find that two subsectors, platform providers and application and software providers, are at the centre of knowledge exchange activity and play a brokerage role as the key knowledge mediator. Then, we categorise mobile firms into five different groups based on the patterns of their network centrality: knowledge keystone players, knowledge-distributing mediators, knowledge-absorbing mediators, catch-up players, and pure knowledge receivers. The categorisation of firms demonstrates that knowledge flows in the mobile industry converge towards a few leading firms, and such patterns are shaping the mobile ecosystem with respect to technological knowledge. The firms categorised as catch-up players have played a brokerage role within their group, while the firms categorised as knowledge keystone players play a brokerage role across different groups.

Implementing technology roadmapping with supplier selection for semiconductor manufacturing companies

The rapid pace of technological innovation in the semiconductor manufacturing industry has necessitated the acquisition of competitive advantage from strategic technology planning. The vital requisite for this is well-timed investment including the replacement of old equipment with advanced new equipment. In such investment, selecting the appropriate semiconductor manufacturing equipment from the appropriate supplier is a key factor for successful technology planning. Therefore, equipment supplier selection should be taken into account in the technology planning of semiconductor manufacturing companies. One of the most widely used tools for technology planning is the technology roadmap (TRM). However, conventional TRMs have not considered the task of supplier selection. To address this limitation, this study proposes an extended, four-layered TRM that adds the layer of equipment supplier to the conventional layers of market, product, and technology. The equipment suppliers to be included in the new layer are selected from the supplier portfolio matrix composed of two performance axes: supplier performance and equipment performance. The candidates of equipment suppliers are placed on the supplier portfolio matrix according to the values of two axes determined by evaluation using the analytic hierarchy process (AHP). The proposed TRM is expected to be useful for technology planning by adding a consideration for equipment supplier selection in semiconductor manufacturing companies.

Measuring efficiency of total productive maintenance (TPM): a three-stage data envelopment analysis (DEA) approach

Total productive maintenance (TPM) is a manufacturing strategy that has been successfully employed globally for the last three decades. A prerequisite for benefiting from TPM is to measure the performance of TPM activities. Although overall equipment effectiveness has widely been used as a performance measure of TPM activities, it is a measure for TPM effectiveness. It is also required to measure the performance of TPM implementation in terms of efficiency. This study intends to measure the efficiency of TPM implementation using data envelopment analysis (DEA) with consideration of the overall process of TPM implementation. Since more and more organisations are increasingly relying on self-directed work team (SDWT) to accomplish organisational tasks in TPM implementation, this study employs SDWT as a unit of analysis. The process of TPM implementation is captured in a three-stage model: stage 1 (from TPM input to TPM intermediate output), stage 2 (from TPM intermediate output to TPM final output), and stage 3 (from TPM input to TPM final output). Every SDWT in every team is evaluated together by DEA for each stage. The relationships between the efficiency scores of the three stages are analysed by correlation analysis. Also, cluster analysis is conducted to identify different types of SDWTs in terms of TPM implementation.

Measuring journal performance for multidisciplinary research: An efficiency perspective

One of the flaws of the journal impact factor (IF) is that it cannot be used to compare journals from different fields or multidisciplinary journals because the IF differs significantly across research fields. This study proposes a new measure of journal performance that captures field-different citation characteristics. We view journal performance from the perspective of the efficiency of a journals citation generation process. Together with the conventional variables used in calculating the IF, the number of articles as an input and the number of total citations as an output, we additionally consider the two field-different factors, citation density and citation dynamics, as inputs. We also separately capture the contribution of external citations and self-citations and incorporate their relative importance in measuring journal performance. To accommodate multiple inputs and outputs whose relationships are unknown, this study employs data envelopment analysis (DEA), a multi-factor productivity model for measuring the relative efficiency of decision-making units without any assumption of a production function. The resulting efficiency score, called DEA-IF, can then be used for the comparative evaluation of multidisciplinary journals’ performance. A case study example of industrial engineering journals is provided to illustrate how to measure DEA-IF and its usefulness.

Uncovering the multidisciplinary nature of technology management: journal citation network analysis

Technology management (TM) is multidisciplinary in nature. This paper investigates the multidisciplinary characteristics of TM through journal citation network analysis. The TM network composed of ten TM specialty journals and relevant journals of other disciplines is constructed based on their citation relationships. In particular, the relatedness index is employed to capture the citation relationships between journals with consideration of different journal sizes. Scrutinizing the network reveals what disciplines have contributed to TM and to what disciplines TM has contributed. The role of TM journals in exchanging knowledge with other disciplines is also identified by using brokerage analysis. TM is shown to have a high degree of interaction with six disciplines: Business and Management, Marketing, Economics, Planning and Development, Information Science, and Industrial Engineering and Operations Research. It is shown that visualizing and analyzing the TM network can provide an excellent overview of its multidisciplinary structure in terms of knowledge flow. This can help TM researchers easily grasp the historical development and fundamental features of TM.

A database-centred approach to the development of new mobile service concepts

This paper proposes a database-centred approach to the systematic development of new mobile service concepts. Keyword vectors are first constructed by applying text mining to the collected mobile application documents. Alternative mobile service concepts are generated by employing morphological analysis to the keyword vectors. Subsequently, by applying conjoint analysis, a portfolio matrix is constructed to evaluate and manage the newly derived mobile service concepts. The working of the proposed approach is provided with the help of a case study of mobile game service concept development by analysing the Apple App Store. The proposed approach can supplement the shortcomings of customer-centred approaches, and it is expected to help service managers and designers in the actual development of new mobile service concepts.

R&D PERFORMANCE MONITORING, EVALUATION, AND MANAGEMENT SYSTEM: A MODEL AND METHODS

Since previous frameworks and methods for evaluation of national R&D have mainly focused on short-term R&D outputs, long-term R&D outcomes have been neglected so that they have failed to be fully utilized and spread. Thus, it is imperative to mirror long-term R&D outcomes in performance evaluation and utilize them through continuous management and monitoring. In response, this paper presents a model of R&D performance monitoring, evaluation, and management system (RPMEMS) for national R&D. The conceptual model of RPMES is presented with its scope, structure, role, and process. It is based on the logic model used in the planning and evaluation of public programs. This study also proposes two methods for relative comparison in the context of RPMEMS: analytic hierarchy process (AHP) and data envelopment analysis (DEA). The proposed model of RPMEMS and methods for relative comparison are expected to be effectively implemented and operated in the practice of management of national R&D.

A hybrid Bass–Markov model for the diffusion of a dual-type device-based telecommunication service: The case of WiBro service in Korea

Abstract Because the increasing complexity of technology embedded in telecommunication services enables services to be provided via various mediums, the vital requisite for forecasting the diffusion of such services is to simultaneously capture different diffusion phenomena for different devices. This paper proposes a new diffusion model for a dual-type device-based service called the hybrid Bass–Markov model. The proposed model is targeted at the service environment where one type of device is new to the market, and the other type has existing competing services. The Bass model is selected to model service diffusion through the former type of device, while the Markov transition model is employed to capture the diffusion through the latter type of device. The hybrid Bass–Markov model is then developed to produce the aggregate demand. The case of the wireless broadband (WiBro) service in Korea is presented to illustrate the proposed model with a policy sensitivity analysis. This research is expected to be the basis of multi-type device-based service forecasting and, ultimately, will help researchers conduct demand forecasting of services offered by several different devices.