Thanwadee Chinda

Investigation of factors affecting a construction waste recycling decision

ABSTRACT The production of high amounts of construction waste is a serious problem in many large cities. Ineffective waste management leads to environmental, health, and safety problems. This paper examines key factors influencing construction waste recycling decisions, utilising the exploratory factor analysis approach and the analytic hierarchy process (AHP). A questionnaire was used to extract key factors and subfactors of construction waste recycling. The analysis of the 107 data sets (27% of the total questionnaires sent) extracted three key factors, namely Economics, Market and Site Activities, and Environment factors. The AHP was then performed using experts’ interviews. The results revealed that the Market and Site Activities factor was the most influential factor in making waste recycling decisions, as it has the highest weight among the three factors. Critical issues of concern were the amount of recycled markets available and the intense competition in the industry. Apart from that, high cost of a specific sorting machine and company’s green image must be appraised before making a decision. Organisations can utilise the developed hierarchy model to make decisions regarding construction waste recycling. The importance weights can also be used as a guideline to prioritise recycling plans to achieve the most benefits.

A Dynamic Model of Productivity Enhancement in the Thai Food Industry

Abstract: The concept of productivity has received growing attention, both in the manufacturing and service industries. This study develops a productivity dynamic model to capture the interactions between the key productivity factors over a period of time, and assess the current productivity maturity level of an organization, so that an organization can plan for productivity improvement. Five productivity factors were used for the productivity dynamic model development. Simulation results reveal that an organization that does not actively address productivity should primarily focus on enhancing the “leadership” and “people” factors to successfully progress through to higher maturity levels. An organization can use the simulation with different strategies to identify the most effective policy to improve its productivity.

A Safety Assessment Approach Using Safety Enablers and Results

Abstract Industrial safety is an important issue in Thailand, and attempts have been made to improve safety performance and accident records. This paper examines key criteria influencing safety improvement. Exploratory factor analysis confirms 9 safety criteria, including 5 “enablers” and 4 “results”, with a total of 47 associated attributes. A safety assessment approach is developed, using those 9 key criteria, to measure an organization’s current safety maturity level. Organizations can use the assessment approach to plan its safety improvement, and progress through to higher maturity levels by focusing on the weakest criteria shown in the assessment results with the lowest scores.

Organizational Factors Affecting Safety Implementation in Food Companies in Thailand

Thai food industry employs a massive number of skilled and unskilled workers. This may result in an industry with high incidences and accident rates. To improve safety and reduce the accident figures, this paper investigates factors influencing safety implementation in small, medium, and large food companies in Thailand. Five factors, i.e., management commitment, stakeholders’ role, safety information and communication, supportive environment, and risk, are found important in helping to improve safety implementation. The statistical analyses also reveal that small, medium, and large food companies hold similar opinions on the risk factor, but bear different perceptions on the other 4 factors. It is also found that to improve safety implementation, the perceptions of safety goals, communication, feedback, safety resources, and supervision should be aligned in small, medium, and large companies.

Factors affecting construction performance: exploratory factor analysis

The present work attempts to develop a multidimensional performance evaluation framework for a construction company by considering all relevant measures of performance. Based on the previous studies, this study hypothesizes nine key factors, with a total of 57 associated items. The hypothesized factors, with their associated items, are then used to develop questionnaire survey to gather data. The exploratory factor analysis (EFA) was applied to the collected data which gave rise 10 factors with 57 items affecting construction performance. The findings further reveal that the items constituting ten key performance factors (KPIs) namely; 1) Time, 2) Cost, 3) Quality, 4) Safety & Health, 5) Internal Stakeholder, 6) External Stakeholder, 7) Client Satisfaction, 8) Financial Performance, 9) Environment, and 10) Information, Technology & Innovation. The analysis helps to develop multi-dimensional performance evaluation framework for an effective measurement of the construction performance. The 10 key performance factors can be broadly categorized into economic aspect, social aspect, environmental aspect, and technology aspects. It is important to understand a multi-dimension performance evaluation framework by including all key factors affecting the construction performance of a company, so that the management level can effectively plan to implement an effective performance development plan to match with the mission and vision of the company.

Structural equation modelling of lower back pain due to whole-body vibration exposure in the construction industry

Whole-body vibration (WBV) exposure is a health hazard among workers, causing lower back pain (LBP) in the construction industry. This study examines key factors affecting LBP due to WBV exposure using exploratory factor analysis and structural equation modelling. The results confirm five key factors (equipment, job related, organizational, personal, social context) with their 17 associated items. The organizational factor is found the most important, as it influences the other four factors. The results also show that appropriate seat type, specific training programme, job rotation, workers’ satisfaction and workers’ physical condition are crucial in reducing LBP due to WBV exposure. Moreover, provision of new machines without proper training and good working condition might not help reduce LBP due to WBV exposure. The results help the construction companies to better understand key factors affecting LBP due to WBV exposure, and to plan for a better health improvement programme.

Key factors influencing management decisions concerning safety equipment selection

The construction industry involves many hazardous activities that may expose workers to a wide variety of health hazards. Selection of construction safety equipment is crucial in ensuring workers’ safety. This article aims to examine key factors influencing management decisions concerning safety equipment selection, utilizing exploratory factor analysis (EFA) and the analytic hierarchy process (AHP). A questionnaire survey is conducted in the construction companies in Bangkok, Thailand. The factor analysis extracts 103 sets of data into six key factors – namely supplier agreements, supplier support, personal, equipment design, safety-related policies and cost value factors – with a total of 20 associated items. The AHP results conclude that the safety-related policies, equipment design and personal factors are the most important factors when selecting construction safety equipment. A construction company can use the study results as a checklist to help assess different safety equipment, and to select the best equipment.

Causal Relationships of Construction Performance Using the Balanced Scorecard

The construction industry is a key industry that makes a significant contribution to the success of the economy of the country. To improve a construction performance, this paper utilizes the balanced scorecard approach to develop a causal loop diagram of construction performance. The results conclude six key factors, including (1) Financial, (2) Customer, (3) Internal Process, (4) Leadership, (5) Employee, and (6) Innovation factors, with a total of 27 associated items. A number of positive and negative loops are summarized to explain interrelationships among the key factors, as well as items, to better understand the construction performance, and plan for performance improvement. The study results will further be used to develop a dynamic model of construction performance, so that a construction company can proceed through to a better performance.

The Development of the Construction and Demolition Waste Dynamic Model

With the higher amount of buildings and infrastructures in Bangkok, Thailand, the number of construction and demolition (C&D) waste is increasing continuously. These wastes, if not completely recycled, will create the environmental problems. This research paper concentrates on the use of a system dynamics modeling technique to develop a C&D waste recycling model. Data and related relationships were generated to develop the simulated equations to simulate the model to reflect real practices of the construction industry in Bangkok, Thailand. The simulation results reveal the improved C&D waste recycled over time.