Search results

One of the most neglected sources of energy loss is streetlights that generate too much light in areas where it is not required. Energy waste has enormous economic and environmental effects. In addition, due to the conventional manual nature of operation, streetlights are frequently seen being turned ‘ON’ during the day and ‘OFF’ in the evening, which is regrettable even in the twenty-first century. These issues require automated streetlight control in order to be resolved. This study aims to develop a novel streetlight controlling method by combining a smart transport monitoring system powered by computer vision technology with a closed circuit television (CCTV) camera that allows the light-emitting diode (LED) streetlight to automatically light up with the appropriate brightness by detecting the presence of pedestrians or vehicles and dimming the streetlight in their absence using semantic image segmentation from the CCTV video streaming. Consequently, our model distinguishes daylight and nighttime, which made it feasible to automate the process of turning the streetlight ‘ON’ and ‘OFF’ to save energy consumption costs. According to the aforementioned approach, geo-location sensor data could be utilised to make more informed streetlight management decisions. To complete the tasks, we consider training the U-net model with ResNet-34 as its backbone. Validity of the models is guaranteed with the use of assessment matrices. The suggested concept is straightforward, economical, energy-efficient, long-lasting and more resilient than conventional alternatives.

This chapter offers an overview of the applications of artificial intelligence (AI) in the textile industry and in particular, the textile colouration and finishing industry. The advent of new technologies such as AI and the Internet of Things (IoT) has changed many businesses and one area AI is seeing growth in is the textile industry. It is estimated that the AI software market shall reach a new high of over US$60 billion by 2022, and the largest increase is projected to be in the area of machine learning (ML). This is the area of AI where machines process and analyse vast amount of data they collect to perform tasks and processes. In the textile manufacturing industry, AI is applied to various areas such as colour matching, colour recipe formulation, pattern recognition, garment manufacture, process optimisation, quality control and supply chain management for enhanced productivity, product quality and competitiveness, reduced environmental impact and overall improved customer experience. The importance and success of AI is set to grow as ML algorithms become more sophisticated and smarter, and computing power increases.

This paper aims to present a systematic approach for knowledge auditing which is composed of a number of stages with the focus on the establishment of an overall framework and customized tools for knowledge auditing.

The systematic approach for knowledge auditing is composed of eight phases: orientation and background study, cultural assessment, in‐depth investigation, building knowledge inventory and knowledge mapping, knowledge network analysis and social network analysis, recommendation of knowledge management strategy, deploying KM tools and building collaborative culture, and continuous knowledge re‐auditing, respectively.

A systematic approach for knowledge auditing is proposed and trial successfully implemented in a railway company. The results show that the systematic knowledge auditing approach yields a number of benefits that include the identification of the critical knowledge and the subsequent recommendations can be derived for better managing the knowledge in the railway company.

Many KM programs failed because the companies themselves lacked the knowledge on KM and their knowledge organization. The practical implementation of the systematic approach for knowledge auditing allows an organization to reveal its KM needs, strengths, weaknesses, opportunities, threats and risks. Hence, appropriate KM strategy can be derived for better managing its knowledge.

The proposed systematic approach for knowledge auditing addresses the shortcomings of some existing knowledge audit approaches which generally lack a systematic approach and have limited practical value for real‐life implementation. The capability of the proposed systematic approach is demonstrated through a successful implementation in a railway company.

The Delphi technique is used to achieve consensus among experts and/or gain judgment on complex matters. This paper aims to discuss the classical Delphi and its advantages and disadvantages in qualitative research, particularly in hospitality.

The classical Delphi is characterized by the involvement of experts and its iterative nature. In an industry with high turnover and limited pools of specialist expertise this can lead to problems of attrition and management of the process. The paper presents two qualitative hospitality research case studies in which the classical Delphi is successfully modified to overcome its limitations.

Identifying potential problems early in the research process enables critical design decisions to be made. Case one used a parallel expert group with similar experience to develop a research instrument for a limited number of prestigious experts well‐acquainted with one another who might have reached specious consensus through channels not accessible to the researcher. Case two enabled the addition of new experts to an expert panel to overcome attrition in successive Delphi rounds.

Despite its growing popularity in social science, Delphi has rarely been used in qualitative hospitality research. The modifications suggested in this paper can enhance the robustness of the classical Delphi technique for qualitative hospitality research.

The paper shows how the classical Delphi technique can be successfully modified for use in qualitative hospitality research.

This study aims to understand the impact of negative supervisor gossip on job performance among South Indian hotel employees. The focus is not just on the direct influence, but also on the mediating role of feedback-seeking behaviour (FSB) and the moderating effects of the agreeableness trait.

Through purposive sampling, data was garnered from South Indian hotel employees. Comprehensive analyses were performed using partial least squares structural equation modelling.

The analysis shows that FSB plays a mediating role in the positive relationship between negative supervisor gossip and job performance. In addition, the influence of gossip on FSB and subsequent job performance was more pronounced for employees with high agreeableness.

This research underscores the complex interplay between negative supervisor gossip and job performance, revealing that such gossip can catalyze FSB process in employees. It suggests that under certain conditions, negative gossip can be transformed into a constructive force that enhances job performance, challenging traditional perceptions of gossip in the workplace.

The findings underscore the importance of understanding the effects of workplace dynamics, like supervisor gossip, on employee behaviour and performance. Recognizing the influence of individual personality traits, such as agreeableness, can guide management strategies for fostering a productive work environment.

This research sheds light on the intricate interplay between negative supervisor gossip, FSB and agreeableness, offering a novel perspective on their combined impact on job performance. It not only enriches the existing literature on workplace communication but also broadens the understanding of the role of personality traits in shaping employee responses and outcomes.

Browsing knowledge documents in a peer-to-peer (P2P) environment is difficult because knowledge documents in such an environment are large in quantity and distributed over different peers who organize the documents according to their own views. This paper aims to propose a method for constructing a personal knowledge map for a peer to facilitate knowledge browsing and alleviate information overload in P2P environments.

The research presents a method for constructing a personal knowledge map. The method adopts an ontology-concept-tree-based classification algorithm to recognize a peer’s personal knowledge structure and construct a personal knowledge map, and uses a self-organizing map algorithm to cluster and visualize the knowledge documents. The correctness of the created knowledge map is evaluated with a collection of abstracts of academic papers.

The method for constructing a personal knowledge map is the main finding of this research. The evaluation shows that the created knowledge map is good in quality.

The proposed method provides a way for P2P platforms to understand their users’ knowledge background, as well as to improve the P2P platform environment. However, the proposed method will not help a peer when he has nothing in his individual knowledge document repository (i.e. the “cold start” problem). The method also requires a relatively good ontology base for a P2P document sharing system to use the method effectively.

It is novel that the proposed method organizes the knowledge documents related to a peer’s knowledge background into a personal knowledge map. Moreover, the created knowledge map combines the advantages of a hierarchical display and a map display. It has values for a distributed P2P environment to facilitate users’ knowledge browsing and to alleviate information overload.

The purpose of this article is to empirically examine the relationship between managers' emotional exhaustion and the ethnic diversity, workload requirements, and friendship ties within their work-groups.

The research employs a full-network sample of all managers from an indigenously owned ethnically diverse IT firm located in the Caribbean island nation of Trinidad and Tobago. Using a social network design within a regression model, the relationship between managerial power and operational workload and the burnout dimension of emotional exhaustion is initially examined as a baseline model. Work-group ethnicity and friendship ties are then examined as moderators to this relationship. The authors then examine the role of work-group ethnicity and friendship ties as a buffer mechanism using an efficient frontier analysis where managers act as decision-making units.

The study indicates that ethnic diversity acts more as a “negative moderator” to emotional exhaustion, while friendship ties act as both a “positive moderator” and “buffer” to work-related emotional exhaustion.

This is one of the few empirical studies that has examined the issues of ethnic diversity and burnout using social network and efficient frontier methodologies. This is also one of the first empirical studies to investigate these issues using an in-depth, full-sample case study of actual, real-work network relationships.

While considerable scholarly attention has been given to “millennials” (those born between 1981 and 1997), little is known of this generation’s ability to influence healthcare organizations and managerial roles in particular. This paper aims to clarify why millennials enter the healthcare management field and how their motivations correlate with preferences for working in various healthcare sectors and with various patient populations.

Survey data were collected from 107 millennials pursuing bachelor degrees in healthcare management by using a modified version of the multidimensional work motivation scale. Further data were collected on millennials’ preferences for working in various healthcare sectors and with various patient populations. Correlational analyses were conducted to examine the relationship between types of motivation and workplace preferences. Cross-cultural differences were also examined within this generational set.

Results indicate a significant positive relationship between intrinsic motivation and preferences for working on the payer side of the industry and within finance and IT functions. Findings also reveal a significant positive relationship between prosocial motivation and preferences for working with more vulnerable patient populations. Variance in work motivation among cultural sub-sets of millennials suggests different upbringings, or alternatively, cultural relativity of the motivational constructs themselves.

Despite offering key insights into the next generation of healthcare managers, this study is limited by a sample of millennials from one large, metropolitan university in the USA and thus may not represent the views of all millennials.

To select, retain and develop the next generation of healthcare managers, it is incumbent upon organizations to better understanding millennials’ motivations and preferences.

This study is the first of its kind to illuminate the motivations and preferences that underpin a key and growing segment of the healthcare workforce. Millennials, now the largest and most diverse generation on the planet, are poised to change the landscape of health care.

This paper aims to highlights the importance of knowledge management in modern organizations.

Presents a systematic approach to knowledge auditing at Hong Kong‐based Kowloon‐Canton Railway Corporation.

Contends that many knowledge‐management schemes fail because the companies themselves lack a systematic approach to knowledge auditing. Highlights the importance of analyzing knowledge‐management needs, strengths, weaknesses, opportunities, threats and risks.

Highlights the importance of management creating an environment to promulgate, motivate and encourage employees to collaborate and share knowledge.

Argues that people are the most efficient carriers of knowledge where knowledge is highly tacit and difficult to codify. As a result, the organization can put effort into areas such as increasing the willingness of the employees to share information related to their job. This can be done through an incentive scheme.