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Article
Publication date: 15 December 2003

F. Johnny Deng, Kamal M. Haddad and Paul D. Harrison

This study aims to advance the understanding, in a cross‐cultural context, of the roles that ethical vs. self‐interest considerations play in project continuation decisions…

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Abstract

This study aims to advance the understanding, in a cross‐cultural context, of the roles that ethical vs. self‐interest considerations play in project continuation decisions. Fifty‐eight executive MBA students from the People’s Republic of China (PRC) completed a project continuation decision using an instrument previously employed by Harrell and Harrison (1994) on U.S. subjects, and Harrison, Chow, Wu and Harrell (1999) on Chinese nationals from Taiwan. Results indicated that while the PRC subjects generally had a lower tendency than these other groups to continue an unprofitable project, they still tended towards continuance. Further analysis revealed that the PRC subjects’ decisions were motivated by an emphasis on their self‐interest as well as ethical considerations. The role of self interests in the PRC subjects’ decisions seems consistent with recent claims that China’s new market ethic is shifting people towards emphasizing their own economic welfare over that of the collective entity. Also of substantive interest was that as compared to their U.S. counterparts, the PRC subjects’ ethical reasoning had a different structure. The relative impacts of their ethical reasoning dimensions also differed from those from their U.S. counterparts.

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Managerial Finance, vol. 29 no. 12
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 3 May 2011

Neale G. O'Connor, F. Johnny Deng and Jingsong Tan

The purpose of this paper is to investigate the influence of liberalization forces, political constraints (on labor decisions) and formal control mechanisms (i.e. delegation of…

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Abstract

Purpose

The purpose of this paper is to investigate the influence of liberalization forces, political constraints (on labor decisions) and formal control mechanisms (i.e. delegation of decision authority, objective performance measurement and merit‐based rewards) on the performance of Chinese State‐owned enterprises (SOEs).

Design/methodology/approach

A survey instrument was used to collect data from functional managers representing over 500 SOEs. Structural equation modeling was used to analyze the data.

Findings

The findings revealed significant and positive path relationships between liberalization forces and each of the formal control mechanisms, leading to firm performance. The findings also reveal that political constraints have a significant and negative path relationship with objective performance measures and firm performance.

Originality/value

The evidence provided in this study adds to our understanding of the role the institutional environment plays in the structuring and management of the firm in transitional economies. The topic is of interest, given the pace of modernization of firms in emerging economies, and the differences in the institutional “rules of the game” that exist compared with developed economies. Both of these forces have the potential to affect not only the management control practices in emerging economy firms, but also other firms that do business with them.

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Pacific Accounting Review, vol. 23 no. 1
Type: Research Article
ISSN: 0114-0582

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Article
Publication date: 8 September 2022

Johnny Kwok Wai Wong, Mojtaba Maghrebi, Alireza Ahmadian Fard Fini, Mohammad Amin Alizadeh Golestani, Mahdi Ahmadnia and Michael Er

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes…

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Abstract

Purpose

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.

Design/methodology/approach

To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.

Findings

The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.

Originality/value

The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

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Construction Innovation , vol. 24 no. 2
Type: Research Article
ISSN: 1471-4175

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Article
Publication date: 1 June 2023

Johnny Kwok Wai Wong, Fateme Bameri, Alireza Ahmadian Fard Fini and Mojtaba Maghrebi

Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically…

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Abstract

Purpose

Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.

Design/methodology/approach

A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.

Findings

The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.

Originality/value

The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.

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Construction Innovation , vol. 25 no. 2
Type: Research Article
ISSN: 1471-4175

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Article
Publication date: 20 December 2022

Biyanka Ekanayake, Alireza Ahmadian Fard Fini, Johnny Kwok Wai Wong and Peter Smith

Recognising the as-built state of construction elements is crucial for construction progress monitoring. Construction scholars have used computer vision-based algorithms to…

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Abstract

Purpose

Recognising the as-built state of construction elements is crucial for construction progress monitoring. Construction scholars have used computer vision-based algorithms to automate this process. Robust object recognition from indoor site images has been inhibited by technical challenges related to indoor objects, lighting conditions and camera positioning. Compared with traditional machine learning algorithms, one-stage detector deep learning (DL) algorithms can prioritise the inference speed, enable real-time accurate object detection and classification. This study aims to present a DL-based approach to facilitate the as-built state recognition of indoor construction works.

Design/methodology/approach

The one-stage DL-based approach was built upon YOLO version 4 (YOLOv4) algorithm using transfer learning with few hyperparameters customised and trained in the Google Colab virtual machine. The process of framing, insulation and drywall installation of indoor partitions was selected as the as-built scenario. For training, images were captured from two indoor sites with publicly available online images.

Findings

The DL model reported a best-trained weight with a mean average precision of 92% and an average loss of 0.83. Compared to previous studies, the automation level of this study is high due to the use of fixed time-lapse cameras for data collection and zero manual intervention from the pre-processing algorithms to enhance visual quality of indoor images.

Originality/value

This study extends the application of DL models for recognising as-built state of indoor construction works upon providing training images. Presenting a workflow on training DL models in a virtual machine platform by reducing the computational complexities associated with DL models is also materialised.

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Construction Innovation , vol. 24 no. 4
Type: Research Article
ISSN: 1471-4175

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Article
Publication date: 30 May 2023

R.V. ShabbirHusain, Atul Arun Pathak, Shabana Chandrasekaran and Balamurugan Annamalai

This study aims to explore the role of the linguistic style used in the brand-posted social media content on consumer engagement in the Fintech domain.

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Abstract

Purpose

This study aims to explore the role of the linguistic style used in the brand-posted social media content on consumer engagement in the Fintech domain.

Design/methodology/approach

A total of 3,286 tweets (registering nearly 1.35 million impressions) published by 10 leading Fintech unicorns in India were extracted using the Twitter API. The Linguistic Inquiry and Word Count (LIWC) dictionary was used to analyse the linguistic characteristics of the shared tweets. Negative Binomial Regression (NBR) was used for testing the hypotheses.

Findings

This study finds that using drive words and cognitive language increases consumer engagement with Fintech messages via the central route of information processing. Further, affective words and conversational language drive consumer engagement through the peripheral route of information processing.

Research limitations/implications

The study extends the literature on brand engagement by unveiling the effect of linguistic features used to design social media messages.

Practical implications

The study provides guidance to social media marketers of Fintech brands regarding what content strategies best enhance consumer engagement. The linguistic style to improve online consumer engagement (OCE) is detailed.

Originality/value

The study’s findings contribute to the growing stream of Fintech literature by exploring the role of linguistic style on consumer engagement in social media communication. The study’s findings indicate the relevance of the dual processing mechanism of elaboration likelihood model (ELM) as an explanatory theory for evaluating consumer engagement with messages posted by Fintech brands.

Details

International Journal of Bank Marketing, vol. 42 no. 2
Type: Research Article
ISSN: 0265-2323

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Article
Publication date: 10 May 2019

Maxwell Fordjour Antwi-Afari, Heng Li, Johnny Kwok-Wai Wong, Olugbenga Timo Oladinrin, Janet Xin Ge, JoonOh Seo and Arnold Yu Lok Wong

Sensing- and warning-based technologies are widely used in the construction industry for occupational health and safety (OHS) monitoring and management. A comprehensive…

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Abstract

Purpose

Sensing- and warning-based technologies are widely used in the construction industry for occupational health and safety (OHS) monitoring and management. A comprehensive understanding of the different types and specific research topics related to the application of sensing- and warning-based technologies is essential to improve OHS in the construction industry. The purpose of this paper is to examine the current trends, different types and research topics related to the applications of sensing- and warning-based technology for improving OHS through the analysis of articles published between 1996 and 2017 (years inclusive).

Design/methodology/approach

A standardized three-step screening and data extraction method was used. A total of 87 articles met the inclusion criteria.

Findings

The annual publication trends and relative contributions of individual journals were discussed. Additionally, this review discusses the current trends of different types of sensing- and warning-based technology applications for improving OHS in the industry, six relevant research topics, four major research gaps and future research directions.

Originality/value

Overall, this review may serve as a spur for researchers and practitioners to extend sensing- and warning-based technology applications to improve OHS in the construction industry.

Details

Engineering, Construction and Architectural Management, vol. 26 no. 8
Type: Research Article
ISSN: 0969-9988

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Book part
Publication date: 2 September 2014

Jens Nordfält, Dhruv Grewal, Anne L. Roggeveen and Krista M. Hill

Retailers increasingly experiment with a wide variety of store elements; this chapter focuses on in-store marketing tactics and reports the results of 12 in-store experiments…

Abstract

Retailers increasingly experiment with a wide variety of store elements; this chapter focuses on in-store marketing tactics and reports the results of 12 in-store experiments conducted in cooperation with different retail chains. Experiments 1–3 address in-store signage (digital, floor) and reveal that digital screens and signage can draw customers toward merchandise and deeper into shopping aisles. Experiments 4–6 explore the impact of the organization of a display (vertical, horizontal, diagonal, waterfall) and generally demonstrate the superiority of vertical organizations of merchandise. In Experiments 7–9, results pertaining to the location of a product in a store highlight the importance of placing merchandise at eye level. With Experiments 10 and 11, the authors reinforce the importance of retail atmospherics (scent, lighting). Finally, Experiment 12 explores product placement and other factors that can enhance the effectiveness of in-store merchandise demonstrations.

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Shopper Marketing and the Role of In-Store Marketing
Type: Book
ISBN: 978-1-78441-001-8

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Article
Publication date: 30 April 2018

Ana Cristina Ferrão, Raquel P.F. Guiné, Paula Correia, Manuela Ferreira, Ana Paula Cardoso, João Duarte and João Lima

A healthy diet has been recognized as one of the most important factors associated with maintaining human health and helping in preventing the development of some chronic…

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Abstract

Purpose

A healthy diet has been recognized as one of the most important factors associated with maintaining human health and helping in preventing the development of some chronic diseases. Therefore, this paper aims to study the perceptions of a sample of university people regarding a healthy diet.

Design/methodology/approach

It was undertaken a descriptive cross-sectional study on a non-probabilistic sample of 382 participants. The data were collected among a sample of Portuguese university people and measured whether people’s perceptions were compliant with a healthy diet.

Findings

The results revealed that the participants’ perceptions were, in general, compliant with a healthy diet (scores between 0.5 and 1.5, on a scale from −2 to +2). However, significant differences were found between age groups (p = 0.004), with a higher average score for young adults, and also between groups with different levels of education (p = 0.025), with a higher score for university degree. The variable chronic diseases also showed significant differences (p = 0.017), so that people who did not have any chronic diseases obtained a higher score.

Originality/value

This study is considered important because it provides evidences about the relation between nutrition knowledge and the perceptions towards a healthy diet. The study allowed concluding that the participants were aware about some nutritional aspects of their diets and, therefore, their perceptions were compliant with a healthy diet. This finding is very relevant because it could be a support for health policy initiatives directed at promoting healthy eating behaviours.

Details

Nutrition & Food Science, vol. 48 no. 4
Type: Research Article
ISSN: 0034-6659

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Article
Publication date: 23 November 2012

Swapan Purkait

Phishing is essentially a social engineering crime on the Web, whose rampant occurrences and technique advancements are posing big challenges for researchers in both academia and…

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Abstract

Purpose

Phishing is essentially a social engineering crime on the Web, whose rampant occurrences and technique advancements are posing big challenges for researchers in both academia and the industry. The purpose of this study is to examine the available phishing literatures and phishing countermeasures, to determine how research has evolved and advanced in terms of quantity, content and publication outlets. In addition to that, this paper aims to identify the important trends in phishing and its countermeasures and provides a view of the research gap that is still prevailing in this field of study.

Design/methodology/approach

This paper is a comprehensive literature review prepared after analysing 16 doctoral theses and 358 papers in this field of research. The papers were analyzed based on their research focus, empirical basis on phishing and proposed countermeasures.

Findings

The findings reveal that the current anti‐phishing approaches that have seen significant deployments over the internet can be classified into eight categories. Also, the different approaches proposed so far are all preventive in nature. A Phisher will mainly target the innocent consumers who happen to be the weakest link in the security chain and it was found through various usability studies that neither server‐side security indicators nor client‐side toolbars and warnings are successful in preventing vulnerable users from being deceived.

Originality/value

Educating the internet users about phishing, as well as the implementation and proper application of anti‐phishing measures, are critical steps in protecting the identities of online consumers against phishing attacks. Further research is required to evaluate the effectiveness of the available countermeasures against fresh phishing attacks. Also there is the need to find out the factors which influence internet user's ability to correctly identify phishing websites.

Details

Information Management & Computer Security, vol. 20 no. 5
Type: Research Article
ISSN: 0968-5227

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