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Article
Publication date: 16 February 2021

Hong Long Chen

Previous studies investigate factors affecting project outcomes. Yet, it has not been fully explored regarding which factors differentiate healthy projects from distressed…

Abstract

Purpose

Previous studies investigate factors affecting project outcomes. Yet, it has not been fully explored regarding which factors differentiate healthy projects from distressed projects in the early stage of the project delivery process. The purpose of this study is to investigate the links between project-planning factors and project outcomes in the closing phase.

Design/methodology/approach

The authors use a longitudinal survey method to examine the predictability of project-planning factors. Subsequently, the authos employ confirmatory factor analysis and hierarchical logit regression to develop project-distress classification models.

Findings

Analysis of 90 capital projects shows that performance variation in the project planning phase explains a substantial portion of project distress at completion. Subsequent univariate logit analysis shows that S5 (quality of scope control system) and Tn1 (new practices and technologies) variables have the strongest predictive abilities. Hierarchical logit analysis further shows that a combination of 15 metrics in the project-distress measurement model produces strong and stable predictive power.

Research limitations/implications

This study assesses how well performance variation in the project-planning phase predicts project distress before construction phase. It does not assume the reported results apply to all types of projects. Nonetheless, future studies could generalize our findings by incorporating more types of projects.

Originality/value

This study takes a systematic approach, combining longitudinal survey, measurement theory and hierarchical logit analysis to identify distressed projects early, offering managers an opportunity to take early corrective actions. Practitioners may use this approach to investigate other types of projects and further refine the project-distress classification model into a project-specific model, thereby reflecting projects' unique characteristics.

Details

International Journal of Managing Projects in Business, vol. 14 no. 5
Type: Research Article
ISSN: 1753-8378

Keywords

Article
Publication date: 17 December 2021

Long Chen, Ming Chen, Hengjie Zhang and Xiao-Ming Yan

The purpose of the study is to examine the crossover effect of leader's role overload on employee's negative affect. More importantly, the stuy will identify the buffering…

Abstract

Purpose

The purpose of the study is to examine the crossover effect of leader's role overload on employee's negative affect. More importantly, the stuy will identify the buffering role of self-concordance goal on the relationship between leader's role overload and employee's negative affect.

Design/methodology/approach

The study builds the crossover impact of leader's role overload on employee's negative affect as well as the moderating effect of self-concordance goal. By a two-wave and paired data from 51 leaders and 225 employees, the study examines the hypothesis using cross-level analysis.

Findings

Results show that leader's role overload tends to reduce negative affect for employees who pursue high-level self-concordance goal and increase negative affect for employees who pursue low-level self-concordance goal.

Practical implications

It is important for employees to get rid of negative affect in the workplace. The study informs managers the benefits of pursuing self-concordance goals in helping employees alleviate the negative effect of leader's role overload.

Originality/value

Findings of the present study can enrich the literature of the crossover process from leader to employee and offer management strategy for enterprises about how to buffer the damaging effect of leader's role overload on employees.

Details

Journal of Managerial Psychology, vol. 37 no. 4
Type: Research Article
ISSN: 0268-3946

Keywords

Article
Publication date: 22 February 2018

Hong Long Chen

Researchers have long sought to understand how risks in supply chains (SCs) affect firm performance. Yet, they have not fully subjected claims of how SC risks affect firm…

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Abstract

Purpose

Researchers have long sought to understand how risks in supply chains (SCs) affect firm performance. Yet, they have not fully subjected claims of how SC risks affect firm financial performance to theoretical and empirical scrutiny. The purpose of this paper is to investigate the links between SC risks and firm financial performance.

Design/methodology/approach

The author analyzes how SC risks affect firm financial performance from the perspective of marginal financial performance (MFP) using survey and financial statement data. The author employs structural equation modeling to examine the hypotheses using 106 Taiwanese listed companies across 20 industries.

Findings

The findings regarding the importance of industry-specific risk, organizational risk, internal business process risk, and demand risk are consistent with prior studies. The author finds that demand risk has an MFP of −0.20, the highest negative effect among the risk variables. The findings also show that industry-specific risk possesses an MFP of −0.16, the second-highest negative effect, despite having no direct effect on financial performance.

Research limitations/implications

This paper examines how SC risks affect MFP via combining survey and financial statement data. It does not assume the reported MFP estimates apply to all businesses in other countries. However, future research could triangulate our findings.

Originality/value

This study combines survey and financial data to analyze how SC risks affect firm financial performance. Specifically, it provides a methodology for estimating quantitative cause-effect relationships between SC risk and firm financial performance, an important topic that receives less research interest in the field of supply chain management.

Details

International Journal of Operations & Production Management, vol. 38 no. 3
Type: Research Article
ISSN: 0144-3577

Keywords

Article
Publication date: 27 January 2022

Chen-Long Li, Chang-Shun Yuan, Xiao-Shuang Ma, Wen-Liang Chen and Jun Wang

This paper aims to provide a novel integrated fault detection method for industrial process monitoring.

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Abstract

Purpose

This paper aims to provide a novel integrated fault detection method for industrial process monitoring.

Design/methodology/approach

A novel integrated fault detection method based on the combination of Mallat (MA) algorithm, weight-elimination (WE) algorithm, conjugate gradient (CG) algorithm and multi-dimensional Taylor network (MTN) dynamic model, namely, MA-WE-CG-MTN, is proposed in this paper. First, MA algorithm is taken as data pre-processing. Second, in virtue of approximation ability and low computation complexity owing to the simple structure of MTN, MTN dynamic models are constructed for each frequency band. Furthermore, the CG algorithm is used to discipline the model parameters and the outputs of MTN model of each frequency band are gained. Third, the authors introduce the WE algorithm to cut down the number of middle layer nodes of MTN, reducing the complexity of the network. Finally, the outputs of MTN model for each frequency band are superimposed to achieve outputs of MTN model, and fault detection is proceeded by the residual error generator based on the difference between the output of MTN model and the actual output.

Findings

The novel proposed method is used to perform fault detection for industrial process monitoring effectively, such as the Benchmark Simulation Model 1 wastewater treatment process.

Originality/value

The novel proposed method has generality and provides considerably improved performance and effectiveness, which is used to perform fault detection for industrial process monitoring. The proposed method has good robustness, low complexity and easy implementation.

Details

Assembly Automation, vol. 42 no. 2
Type: Research Article
ISSN: 0144-5154

Keywords

Case study
Publication date: 13 August 2021

Siew Mui Kong, Rajendran Muthuveloo, Josephine Ie Lyn Chan and Ai Ping Teoh

This paper aims to enable students craft a winning corporate strategy applicable for organizations in various contexts. The practical approach consists of conducting…

Abstract

Learning outcomes

This paper aims to enable students craft a winning corporate strategy applicable for organizations in various contexts. The practical approach consists of conducting scenario planning based on internal and external environment analysis, identifying the winning factor, proposing an implementation strategy of entry and exit strategies, and future customers, and evaluating matching of business ethics and legality.

Case overview/synopsis

Wesley Chen, the executive director and group chief executive officer, has the ultimate challenge of leading his management team to operate from a sole proprietorship management style to a listed large company in the Malaysian Stock Exchange. He identified the gap in the need to craft a winning corporate strategy for business sustainability. The corporate strategy should address expansion of their service offerings and needs to be carefully crafted to suit TopSteel’s risk appetite and overall business strategy. The strategy must also consider the internal and external factors that TopSteel faced with, identify the core competency of TopSteel, build in strategic agility in the implementation plans to address the dynamic business landscape, and most importantly ensure the corporate strategy must be in compliance to ethical and legal standards. The case study documents the one year of transition of TopSteel’s operations with a strong focus on the strategic management process direction for a winning OEM+ model through the use of SWIM concept.

Complexity academic level

This case is suitable for undergraduate or postgraduate programs or even executive courses in strategic management.

Supplementary materials

Teaching Notes are available for educators only.

Subject code

CSS 11: Strategy

Details

Emerald Emerging Markets Case Studies, vol. 11 no. 2
Type: Case Study
ISSN: 2045-0621

Keywords

Article
Publication date: 1 November 2022

Jing-Rong Chang, Venkateswarlu Nalluri, Long-Sheng Chen and Shih-Hsun Chen

This study aims to simultaneously examine customer complaints through the proposed novel Design for Six Sigma (DFSS) model which incorporates of creating the new insurance…

Abstract

Purpose

This study aims to simultaneously examine customer complaints through the proposed novel Design for Six Sigma (DFSS) model which incorporates of creating the new insurance services to win customers' hearts and mind for the insurance industry.

Design/methodology/approach

A novel DFSS research methodology which includes the theory of inventive problem solving (TRIZ), Pugh concept selection, creative product analysis matrix and importance–satisfaction model (I–S Model) was proposed. In addition, a real insurance company case was studied to illustrate the effectiveness of the proposed DFSS model.

Findings

The results of a novel DFSS model not only can establish new services, but also can dramatically reduce the cost of resolving customer complaints.

Practical implications

The findings of this study are useful for insurance companies and other related service providers in devising tailored strategies to offer quality and suitable services to their customers.

Originality/value

This study addresses the paucity of research and marketing gaps through the proposed novel DFSS model for the first time in the insurance industry. These study findings would enable researchers and practitioners to formulate strategies for solving customer complaints effectively and develop new services from time to time.

Details

The TQM Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-2731

Keywords

Article
Publication date: 15 April 2022

Long Chen and Yana Du

Previous studies have vague views about whether employees who are required to complete large amounts of work (i.e. role overload) would proactively create a change in…

Abstract

Purpose

Previous studies have vague views about whether employees who are required to complete large amounts of work (i.e. role overload) would proactively create a change in their job characteristics (i.e. job crafting), because the cognitive mechanism underlying the nexus between role overload and job crafting is unclear. The aim of this study is to identify why and when role overload has an impact on job crafting.

Design/methodology/approach

This study builds a second-stage moderated mediation model. Using a two-wave panel field study of 213 employee–supervisor matched data, this study examines the proposed hypotheses.

Findings

Results show that role overload decreases construal level, which can determine the tendency of employees to focus on the feasibility (low level of construal) or desirability (high level of construal) of behaviors. Goal self-concordance is the degree to which employees pursue their personal goals based on feelings of personal interests and values. The authors find that goal self-concordance guides employees who have higher levels of construal to exert more effort in job crafting. The authors further find that goal self-concordance moderates the mediating role of construal level. Specifically, for employees in pursuit of self-concordant goals, role overload reduces their construal level, resulting in less effort in job crafting. For employees who do not pursue self-concordant goals, role overload decreases their construal level, thereby improving job crafting.

Originality/value

The findings of this study enrich the literature on role overload and job crafting by revealing the mechanism and boundary conditions of the relationship between role overload and job crafting.

Details

Personnel Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0048-3486

Keywords

Abstract

Details

Journal of Facilities Management , vol. 20 no. 3
Type: Research Article
ISSN: 1472-5967

Article
Publication date: 2 May 2017

Yingyu Zhao, Zhenbin Chen, Donglei Liu, Jiapeng Long and Duolong Di

The purpose of this paper is to separate and purify flavonoids existing in the leaves of Sophora japonica by a novel method, macroporous adsorption resin (MAR) mixed-bed…

Abstract

Purpose

The purpose of this paper is to separate and purify flavonoids existing in the leaves of Sophora japonica by a novel method, macroporous adsorption resin (MAR) mixed-bed technology, and the optimal MAR mixed bed was screened based on the adsorption experimental result with the order of single, two, three and four MAR mixed bed separately.

Design/methodology/approach

The adsorption performance of MAR and MAR mixed bed for flavonoids was studied using ultraviolet – visible (UV-VIS) spectrophotometry.

Findings

This research showed that the MAR mixed bed of LZ-54 + LZ-67 with a mass ratio of mLZ-54:mLZ-67 = 1:1 was the optimized combination with the optimal conditions of adsorption (volume V = 140 mL, pH = 5, T = 35°C) and desorption (liquid ratio R = 50 per cent, T = 30°C, pH = 6) obtained, relatively.

Practical implications

This study aims to find an efficient way of separating flavonoids and other components that are useful for human health from Sophora japonica, which is complying with the policy of sustainable development.

Originality/value

This contribution provided a novel way to separate flavonoids from Sophora japonica. Under the optimal conditions, the adsorption rate (F) of MAR mixed bed LZ-54 + LZ-67 to the flavonoids was 63.65 per cent, the desorption rate (D) was 87.31 per cent and the purity was dramatically achieved at 58.17 per cent from 17.67 per cent after a round of adsorption/desorption operation.

Details

Pigment & Resin Technology, vol. 46 no. 3
Type: Research Article
ISSN: 0369-9420

Keywords

Article
Publication date: 18 June 2019

Ying Ma, Kang Ping, Chen Wu, Long Chen, Hui Shi and Dazhi Chong

The Internet of Things (IoT) has attracted a lot of attention in both industrial and academic fields for recent years. Artificial intelligence (AI) has developed rapidly…

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Abstract

Purpose

The Internet of Things (IoT) has attracted a lot of attention in both industrial and academic fields for recent years. Artificial intelligence (AI) has developed rapidly in recent years as well. AI naturally combines with the Internet of Things in various ways, enabling big data applications, machine learning algorithms, deep learning, knowledge discovery, neural networks and other technologies. The purpose of this paper is to provide state of the art in AI powered IoT and study smart public services in China.

Design/methodology/approach

This paper reviewed the articles published on AI powered IoT from 2009 to 2018. Case study as a research method has been chosen.

Findings

The AI powered IoT has been found in the areas of smart cities, healthcare, intelligent manufacturing and so on. First, this study summarizes recent research on AI powered IoT systematically; and second, this study identifies key research topics related to the field and real-world applications.

Originality/value

This research is of importance and significance to both industrial and academic fields researchers who need to understand the current and future development of intelligence in IoT. To the best of authors’ knowledge, this is the first study to review the literature on AI powered IoT from 2009 to 2018. This is also the first literature review on AI powered IoT with a case study of smart public service in China.

Details

Library Hi Tech, vol. 38 no. 1
Type: Research Article
ISSN: 0737-8831

Keywords

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