Supporting shop floor workers with a multimedia task-oriented information system

Tjahjono, Benny

doi:10.1016/j.compind.2009.01.003

Cited by 19 publications

(11 citation statements)

References 11 publications

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“…This model looked at various types of knowledge and their effects on different task units. In similar study Tjahjono (2009) found out multi-media-based information system increased efficiency and productivity of manufacturing operations. Using three industry categories Islam and Shazali (2011) studied degrees of skills, favorable working environment and R&D on manufacturing productivity of labor-intensive industries.…”

Section: Literature Reviewmentioning

confidence: 84%

“…There have been numerous studies been carried out to identify the most influential factors affecting productivity including quality (Lee et al, 2007;Terziovski, 2006), knowledge (Kollberg and Elg, 2011), investment (Mawdesley and Al-Jibouri, 2010), equipment losses (Shirose, 1996), maintenance (Bamber et al, 1999;Ahuja and Khamba, 2008) , working methods (Tjahjono, 2009) and labor quality (San et al (2008). Based on the data collected from UK construction firms Mawdesley and Al-Jibouri (2010) identified five dominant factors including investments in planning and control.…”

Section: Literature Reviewmentioning

confidence: 99%

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A bottom‐up approach for productivity measurement and improvement

Jagoda

Lonseth

2013

International Journal of Productivity and Performance Management

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Purpose -The steady incline in oil prices combined with the recent credit crisis and downturns in financial markets has driven organizations to re-evaluate their manufacturing processes and bottom line. The purpose of this paper is to suggest a bottom-up approach that may be used by firms in planning, managing and forecasting productivity improvements. Design/methodology/approach -A multiple-case study approach was used: two comprehensive cases and seven short cases were used to illustrate the model. Findings -The lack of understanding of the relationship between productivity, profitability and performance has led to the application of piece-meal solutions for problems in productivity. Bottom-up approach in improving productivity will provide better results than top-down approach. Originality/value -This paper describes the bottom-up approach which has been successfully used for managing productivity improvement initiatives.

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Section: Literature Reviewmentioning

confidence: 84%

Section: Literature Reviewmentioning

confidence: 99%

A bottom‐up approach for productivity measurement and improvement

Jagoda

Lonseth

2013

International Journal of Productivity and Performance Management

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“…Figure 5.3 serves to highlight the challenges surrounding levels of analysis that must be resolved to effectively advance TTF research. For example, there would seem to be some value in improving our explanations of how individual level TTF Dishaw and Strong (1999), Klopping and McKinney (2004), Norzaidi et al (2009Norzaidi et al ( , 2007, Tjahjono (2009 (continued) Dishaw and Strong (1998a, b, 1999, Goodhue et al (1997), Goodhue and Thompson (1995), Klopping and McKinney (2004), Kositanurit et al (2006), Lam et al (2007), Huang (2008, 2009), Nance and Straub (1996), Norzaidi et al (2009Norzaidi et al ( , 2007 leads to organizational performance benefits. The literature has, thus far, tended to rely on user perceptions of performance such as perceptions of whether a technology improves productivity.…”

Section: Summary Frameworkmentioning

confidence: 93%

Task-Technology Fit Theory: A Survey and Synopsis of the Literature

Furneaux

2011

Integrated Series in Information Systems

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Over the past decade there has been a notable increase in the use of Task-Technology Fit (TTF) theory within the field of information systems. This theory argues that information system use and performance benefits are attained when an information system is well-suited to the tasks that must be performed. As such, it seeks to offer an account of two of the key outcomes of interest to information systems (IS) researchers. Continued interest in the application of TTF theory is therefore expected and, as a result, the following chapter aims to provide a brief overview of the theory and how it has been applied in prior work. Readers are presented with an overview of the diverse range of research contexts and methodologies that have been used to test and extend TTF theory. Key outcomes of interest to TTF researchers are also examined as are the various approaches that researchers have used to operationalize the notion of TTF. It is hoped that this overview will serve as a sound basis for future research and simultaneously help to ensure that IS research does not continue to tread the same ground. Keywords IntroductionRecognition that information systems need to be well-suited to their intended tasks extends back at least as far as the origins of the information systems (IS) discipline (Kanellis et al. 1999). Media richness theory has, for example, been founded on the premise that the decision to use a particular communication technology will be made based on the nature of the specific message to be conveyed (Daft et al. 1987). Similarly, the need for the capabilities of information systems to be suited to their tasks has been highlighted by early research examining information systems adoption (e.g., Thompson et al. 1991). Explicit, formal specification of task-technology fit (TTF) theory did not, however, occur until the publication of three seminal articles during the mid-1990s (Goodhue 1995;Goodhue and Thompson 1995;Zigurs and Buckland 1998). Since the time of these publications, the theory of TTF has been applied extensively to understanding the use of information systems and the consequences of this use in a broad range of personal and professional contexts. Recent years have been characterized by a notable increase in the use of TTF as evidenced by the number of publications incorporating the theory that have appeared in peer-reviewed journals. This trend suggests growing interest in the theory and how it can be applied to understanding the problems of interest to IS researchers. As a result, the following discussion presents a brief overview of task-technology fit theory and summarizes how it has been applied in prior work. In providing a comprehensive synopsis of the current state of TTF research, this chapter offers important guidance to researchers interested in pursing research that draws on the theory. It is hoped that the resulting understanding will serve as a sound basis for new and innovative applications and extensions of TTF theory within the field of information systems as well as within o...

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“…Besides, Dishaw et al 12 suggested TAM and TTF models combined that demonstrated task -technology fit to have a significant impact on perceived usefulness. Based on TTF, TAM and TTF models combined and some studies such as Norzaidi et al (2009), Tjahjono (2009), Chang (2008), Wu et al (2007), Klopping and McKinney (2004), Dishaw and S trong (1999), Goodhue (1995) 9,10,19,[29][30][31][32][33] hypothesis H2 is stated as follows: H2: The task -technology fit has a positive effect o n the perceived usefulness in ERP environment. Based on three theories, namely TAM and TTF models combined, ECM (Expectation-Confirmation Model) 14 and DeLone and McLean IS Success Model (2013) 2 , this study developed the hypothesis H3.…”

Section: Perceived Usefulnessmentioning

confidence: 99%

The role of perceived usefulness in the relationship between task — technology fit and individual job performance in ERP implementation — evidence from Vietnam’s enterprises

Nhi

Lam

2020

Sci. Tech. Dev. J. Econ. Law. Manag.

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In this context, the aim of the study was to examine the role of perceived usefulness in the relationship between individual job performance and task – technology fit in ERP environment. The study was done by 225 individuals. The results of the PLS_SEM analysis reveal ed that task — technology fit was significantly and positively related to perceived usefulness and individual job performance in ERP environment. Furthermore, perceived usefulness was significantly to individual job performance in ERP context. The results of this study added to the empirical evidence in the application of background theories including TTF, TAM and TTF models combined, DeLone and McLean IS Success Model, and ECM. Besides, they also added to the theoretical background of ERP's success. Furthermore, they support for companies who are planning to use ERP systems and the ERP vendors and implementers become more knowledgeable about ERP's success and forecast success when using ERP systems. Based on these results, the enterprise can plan the application to improve the efficiency of ERP systems. At the same time, the ERP vendors and developers can better advise and support their customers when delivering and deploying ERP systems

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Supporting shop floor workers with a multimedia task-oriented information system

Cited by 19 publications

References 11 publications

A bottom‐up approach for productivity measurement and improvement

A bottom‐up approach for productivity measurement and improvement

Task-Technology Fit Theory: A Survey and Synopsis of the Literature

The role of perceived usefulness in the relationship between task — technology fit and individual job performance in ERP implementation — evidence from Vietnam’s enterprises

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