Ping-Yu Hsu

Development of measures to assess the ERP adoption of small and medium enterprises

Purpose – The purpose of this paper is to contribute to the development of measures to assess the ERP adoption of small and medium-sized enterprises. Design/methodology/approach – The paper follows Churchill’s guideline for developing measures that have desirable reliability and validity. The pilot data are used to develop a proper measurement. The survey data, based on the 126 valid responses of 328 companies, are analysed by structural equation modelling (SEM) statistical methods. Findings – The paper finds that the dimensions affecting ERP adoption show that characteristics of the CEO and perceived benefits possess positive effects on ERP adoption, while cost and technology have negative effects on ERP adoption. However, only “perceived benefits” is a significant dimension. It is surprising that the cost of the ERP system does not significantly affect ERP adoption. Research limitations/implications – The paper shows that the sample size should be taken into consideration when generalising the findings, and extended data and measures are required for further in-depth investigation in specific areas. Practical implications – The paper points out that the managers of SMEs with limited resources can find many ways to get more resources from governments. Government managers should be more realistically set the goal of helping firms in a healthy condition to adopt e-business instead of setting the goal of improving the e-business readiness of all SMEs. To help all CEOs of SMEs to realise the potential benefits, governments can work with academic research groups to set up forums and workshops to broadcast knowledge. Originality/value – The paper develops measurements to assess the ERP adoption of small and medium-sized enterprises. The results offer practical help for government managers to better understand ERP adoption with institutional help in Taiwan. Meanwhile, researchers interested in

Identification of critical failure factors in the implementation of enterprise resource planning (ERP) system in Taiwan's industries

In this research, we aim at exploring the critical factors causing failure in the implementation of the enterprise resource planning (ERP) system. Relevant literature indicates the existence of critical failure factors (CFFs) in the implementation of ERP systems that support different organisation levels. As the CFFs do not go through data collection verification from the organisations that implement ERP systems, we endeavour to contribute to the ERP studies by presenting valid findings obtained from a survey on top management, ERP project managers, key users and end users from companies in Taiwan. Our results identify time frame and project management, personnel training and change management as the CFFs in the implementation of ERP systems in Taiwan. If firms can focus and improve on their management of these failure factors, they can increase the rate of success in the implementation of the ERP system.

Mining hybrid sequential patterns and sequential rules

The problem addressed in this paper is to discover the frequently occurred sequential patterns from databases. Basically, the existing studies on finding sequential patterns can be roughly classified into two main categories. In the first category, the discovered patterns are continuous patterns, where all the elements in the pattern appear in consecutive positions in transactions. The second category is to mine discontinuous patterns, where the adjacent elements in the pattern need not appear consecutively in transactions. Although there are many researches on finding either kind of patterns, no previous researches can find both of them. Neither can they find the discontinuous patterns formed of several continuous sub-patterns. Therefore, we define a new kind of patterns, called hybrid pattern, which is the combination of continuous patterns and discontinuous patterns. In this paper, two algorithms are developed to mine hybrid patterns, where the first algorithm is easy but slow while the second complicated but much faster than the first one. Finally, the simulation result shows that our second algorithm is as fast as the currently best algorithm for mining sequential patterns.

Improving SQL with generalized quantifiers

A generalized quantifier is a particular kind of operator on sets. Coming under increasing attention recently by linguists and logicians, they correspond to many useful natural language phrases, including phrases like: three, Chamberlins three, more than three, fewer than three, at most three, all but three, no more than three, not more than half the, at least two and not more than three, no students, most male and all female, etc. Reasoning about quantifiers is a source of recurring problems for most SQL users, and leads to both confusion and incorrect expression of queries. By adopting a more modern and natural model of quantification these problems can be alleviated. We show how generalized quantifiers can be used to improve the SQL interface.<<ETX>>

βP: A novel approach to filter out malicious rating profiles from recommender systems

Recommender systems are widely deployed to provide user purchasing suggestion on eCommerce websites. The technology that has been adopted by most recommender systems is collaborative filtering. However, with the open nature of collaborative filtering recommender systems, they suffer significant vulnerabilities from being attacked by malicious raters, who inject profiles consisting of biased ratings. In recent years, several attack detection algorithms have been proposed to handle the issue. Unfortunately, their applications are restricted by various constraints. PCA-based methods while having good performance on paper, still suffer from missing values that plague most user-item matrixes. Classification-based methods require balanced numbers of attacks and normal profiles to train the classifiers. The detector based on SPC (Statistical Process Control) assumes that the rating probability distribution for each item is known in advance. In this research, Beta-Protection (@bP) is proposed to alleviate the problem without the abovementioned constraints. @bP grounds its theoretical foundation on Beta distribution for easy computation and has stable performance when experimenting with data derived from the public websites of MovieLens.

A Petri Net Approach to Support Resource Assignment in Project Management

Petri nets have long been used in modeling and simulating project execution because of their great capability to describe concurrent activities and simulate the evolvement of processes. Although a number of extended Petri net models have been proposed to model and simulate resource sharing and activity dependence in projects, none of them has ever included a resource assignment mechanism into their models. Because resource assignments influence how limited resources are allocated among conflicting activities, they may heavily affect the availability of resources and the execution of projects. Therefore, a model without considering resource-sharing and resource assignment strategies may lead to a misunderstanding about project scheduling, resource consumption behaviors, and estimated project time. Accordingly, this paper proposes a new extended Petri net model that can describe how resources are shared and assigned among concurrent activities of multiple projects. The proposed model is named as resource assignment Petri net (RAPN), which extends an object composition Petri net with new places, transitions, attributes, and firing rules to model resource-sharing and resource assignment strategies. Finally, we prove that RAPN can correctly model the resource consumption behaviors of projects and can correctly compute the total elapsed time of projects.

Advanced sales and operations planning framework in a company supply chain

Traditional sales and operations planning (S&OP) focuses on balancing company supply and demand, and is utilised utilised to align plans that support a business-strategic goal. An obvious drawback of previous decision models is their lack in considering the supply chain network. This article proposes a new global S&OP planning framework to integrate four supply chain stages of demand, purchasing, production and transportation with different planning strategies. Model applicability is tested by a real life case. Several simulation scenarios are conducted to evaluate the effectiveness and efficiency of the proposed model and heuristics. This study adopts the integrated method as a decision support tool, thereby enhancing coordination between financial and physical activities.

An effective approach for content delivery in an evolving intranet environment – a case study of the largest telecom company in taiwan

Being the dominant telecommunication company in Taiwan, ChungHwa Telecom Co., Ltd., CHT is her symbol listed on the New York Stock Exchange, provides major communication services to more than 23 million people living in Taiwan. CHT has vast number of software developed on client-server or web-based architectures with client software installed in more than ten thousand client computers spreading over the entire nation. Since telecommunication industry evolved in fast pace, the software functions are constantly changing. The changes have to be reflected in all client software before new services can be launched. Thus, the cost and time in distributing contents to client computers has become a major concern in CHT. To improve the efficiency of contents distribution, this research helps CHT develop new software to automatically distribute contents to client computers. To minimize the chance of system locks and balance contents distribution loading, in the new system, each dispatching server sends update contents to no more than three other servers. The contents are delivered with hybrid routing strategy that combines both fixed and adaptive routing strategies. With its low error rate and speedy distribution, the new system reduces the man-minutes per year required to manage the contents distribution of a client server system from 14,227.2 minutes to 1,144 minutes, namely reduces 92% of the time. The user satisfaction of the system was also found to be above 80% among six factors of the measurement designed by Bailey, et al. [1].

Knowledge sharing intention in the United States and China: a cross-cultural study

In today’s knowledge-based economy, most of the knowledge-sharing studies have investigated the effects of cultural values at the national level. However, individual beliefs and behaviors might also be influenced and modified by individual cultural values. To understand the effects of cultural values, cultural effects at both the individual and country levels should be considered. This study is to investigate the integrative effects of the individual’s and country’s cultural values on knowledge sharing. We examine motivational factors affecting knowledge-sharing intentions based on social exchange theory and incorporate individualism/collectivism and uncertainty avoidance as moderators. On the basis of a survey of 394 employees conducted in the United States and China, the results show that rewards are significantly related to knowledge-sharing intentions for Chinese employees but not for American employees. Reciprocity and knowledge self-efficacy significantly impact knowledge-sharing intentions in the two countries. Our results also demonstrate that the individual’s and country’s cultural values play important roles in knowledge sharing. In the United States, individualism/collectivism is found to moderate the relationship between rewards and knowledge-sharing intentions. In China, individualism/collectivism is found to moderate the relationship between reputation and knowledge-sharing intentions, while uncertainty avoidance is found to moderate the relationship between knowledge self-efficacy and knowledge-sharing intentions.

An empirical study of managers' usage intention in BI

In a changing business environment, data within and around organizations rapidly accumulate. In recent years, many organizations have implemented business intelligence (BI) to manage and refine the vast stocks of data. The effective use of BI can support managers to make faster and better decisions. The goal of this study is to investigate how to increase a manager’s intention to read information and to create reports. Based on the technology acceptance model, a research model is developed and tested to assess the factors (i.e., usefulness and ease of use) affecting a manager’s intention to use BI. In addition, the relationship between the intention to read information and the intention to create reports is linked using Dholakia and Bagozzi (D&B) model. A survey of 271 managers supports the proposed model. The empirical results show that the usefulness of BI directly and indirectly affects the intention to read information. Both the reading and creating interfaces of BI affect the intention to read information and the intention to create reports, respectively. The intention to read information positively and significantly affects the intention to create reports. Given the empirical findings, this study provides theoretical and managerial insights for organizations and managers.