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.
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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…
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.
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Researchers in supply chain (SC) payment management have long sought to understand how project contractors, project owners, specialist contractors, and suppliers behave in the…
Abstract
Purpose
Researchers in supply chain (SC) payment management have long sought to understand how project contractors, project owners, specialist contractors, and suppliers behave in the context of negotiating payment terms that improve contractors' SC cash flow.
Design/methodology/approach
Using a single case study approach, semi‐structured interviews with contract and project managers identify behavioral patterns. An analysis of categorical experiments and Spearman's correlation tests on 118 surveys from Taiwanese project contracting corporations generalizes the case findings.
Findings
The findings suggest that payment terms of project owners, specialists, and suppliers have an important impact on contractors' working capital. The findings also reveal that contractors pass project owners' payment terms down to specialists and suppliers, suggesting that contractors' behavior depends on that of the project owners.
Research limitations/implications
This paper generalizes the case findings via surveys, but does not assume that the reported behavior patterns apply to all business enterprises. Future research could triangulate the findings.
Originality/value
This study combines qualitative and quantitative methods to understand how the project owner‐contractor‐supplier (or owner‐contractor‐specialist) triad behaves. Particularly, it focuses on an economic sector – real estate and construction – that receives less research interest than processing or manufacturing.
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Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior…
Abstract
Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.
Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.
TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.
The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.
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Yat‐Hung Chiang, Eddie W.L. Cheng and Patrick T.I. Lam
This paper aims to identify a set of potential determinants of capital structure. By knowing the key determinants, it is possible to understand how building contractors make…
Abstract
Purpose
This paper aims to identify a set of potential determinants of capital structure. By knowing the key determinants, it is possible to understand how building contractors make decisions on capital structure.
Design/methodology/approach
A questionnaire survey was conducted to solicit Hong Kong building contractors' view on the predictive power of a set of financial ratios on capital structure. Each of the seven proxies of capital structure was regressed on the five financial ratios. The usual diagnostic tests (i.e. Durbin‐Watson and variance inflation factor tests) and plots of residuals and normality were carried out to ensure that assumptions of linear regression analysis were met. To validate the findings, eight contractors were further interviewed.
Findings
Both measures of long‐term debts (i.e. “long‐term debt divided by total assets” and “long‐term debt divided by total debt”) are proven to be related to “tangibility” significantly. Also, perceived growth opportunities are significantly related to three proxies for capital structure (i.e. total debt to capital, long‐term debt and long‐term leverage).
Research limitations/implications
Further research should be undertaken to improve the quality of data and to enrich the understanding of how contractors define their capital structures.
Originality/value
Despite a plethora of research having been done by financial researchers, there are very few relevant papers in the construction field. This paper is intended to explore how building contractors made decisions on capital structure.
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Hua Deng and Wendong Liu
This study aims to inform prospective listing firms, investors and regulators of the unique drivers of Chinese initial public offering (IPO) pricing on the Hong Kong Exchange.
Abstract
Purpose
This study aims to inform prospective listing firms, investors and regulators of the unique drivers of Chinese initial public offering (IPO) pricing on the Hong Kong Exchange.
Design/methodology/approach
Using a hand-collected IPO dataset, we investigate whether information uncertainty or investor exuberance drives underpricing and Chinese IPOs’ performance from 2002 to 2015, including 114 state-owned enterprises (SOEs).
Findings
Contrasting with the “listing bubble” in the China domestic stock market, generated by the overoptimism of retail investors, we highlight a “placing bubble” among Chinese firms listed in Hong Kong. This is driven by institutional investors’ buoyant demand for Chinese IPO shares, particularly those of SOEs. Chinese listing firms employ discreet earnings management strategies with their working capital accounts to smooth pre-IPO earnings, which becomes apparent to the market only in the long term.
Originality/value
This study is the first to examine the pricing of sought-after Chinese IPOs among international investors, who face various restrictions when investing in the Chinese domestic stock market. Additionally, it is the first study to measure earnings management using hand-collected pre-IPO data in IPO underpricing studies.
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Three types of industrial buyer-seller relational process models are available: joining theory, stage theory, and state theory. However, historically, these models have developed…
Abstract
Three types of industrial buyer-seller relational process models are available: joining theory, stage theory, and state theory. However, historically, these models have developed based on the knowledge and cultural context of the Western world. Several researchers note that national culture may have an impact on international industrial buyer-seller relationships. Including culture in the models is highly important, especially as the business environment is increasingly more global and different countries have different business cultures. The goal of this paper is to define the most suitable industrial buyer-seller relational process models for describing relationships in various contexts. The paper includes a through literature review and a single case study in order to reach this objective. A new state theory model evolved during the research. It consists of two beginning states: searching and starting; four purely middles states: constant/static, decline, growth, and troubled; and a purely end state: termination. The state of dormant/inert is both a middle state and an end state, that is, when the relational actors are not in contact does not mean that the relationship has ended, but instead, for example, new legislation may have been implemented, which requires the actors to evaluate their relationship and its future. A relationship goes through the two beginning states in the order mentioned above, but after that, any state may occur.
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Jun Huang, Haijie Mo and Tianshu Zhang
This paper takes the Shanghai-Shenzhen-Hong Kong Stock Connect as a quasi-natural experiment and investigates the impact of capital market liberalization on the corporate debt…
Abstract
Purpose
This paper takes the Shanghai-Shenzhen-Hong Kong Stock Connect as a quasi-natural experiment and investigates the impact of capital market liberalization on the corporate debt maturity structure. It also aims to provide some policy implications for corporate debt financing and further liberalization of the capital market in China.
Design/methodology/approach
Employing the exogenous event of Shanghai-Shenzhen-Hong Kong Stock Connect and using the data of Chinese A-share firms from 2010 to 2020, this study constructs a difference-in-differences model to examine the relationship between capital market liberalization and corporate debt maturity structure. To validate the results, this study performed several robustness tests, including the parallel test, the placebo test, the Heckman two-stage regression and the propensity score matching.
Findings
This paper finds that capital market liberalization has significantly increased the proportion of long-term debt of target firms. Further analyses suggest that the impact of capital market liberalization on the debt maturity structure is more pronounced for firms with lower management ownership and non-Big 4 audit. Channel tests show that capital market liberalization improves firms’ information environment and curbs self-interested management behavior.
Originality/value
This research provides empirical evidence for the consequences of capital market liberalization and enriches the literature on the determinants of corporate debt maturity structure. Further this study makes a reference for regulators and financial institutions to improve corporate financing through the governance role of capital market liberalization.
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This study aims to investigate the cointegration and causality relationships between Hong Kong’s residential property price and stock price, using quarterly data, from the 1st…
Abstract
Purpose
This study aims to investigate the cointegration and causality relationships between Hong Kong’s residential property price and stock price, using quarterly data, from the 1st quarter of 1980 to the 3rd quarter of 2015.
Design/methodology/approach
In contrast to other studies, the cointegration test used is the autoregressive distributed lag (ARDL) cointegration (bounds testing) approach of Pesaran et al. (2001) that based on the estimation of an unrestricted error correction model and the causality test is based on non-causality test of Granger et al. (2000). Moreover, this research employs recursive least square procedures and Chow (1960) breakpoint test to detect unknown structural break and variation of relationships between residential property and stock price over the whole sample period.
Findings
The results of ARDL cointegration tests running from stock to residential property markets provide strong evidence to support the hypothesis that the stock and residential properties are cointegrated. The results of Granger et al. (2000) non-causality test support the view of wealth effect that stock price has an important causal effect on residential property price in Hong Kong but not vice versa. In addition, the results of recursive ordinary least squares coefficients estimates and Chow (1960) test (breakpoint test) for structural instability confirm the variation of the relationships between stock and residential property markets over the sample period.
Research limitations/implications
The empirical results from cointegration and causality tests suggest that the residential asset returns are better predicted by including the lagged difference values of stock price.
Originality/value
This is the pioneering study to examine the cointegration and causality study of stock and residential property price in Hong Kong by employing Pesaran ARDL cointegration approach and Granger non-causality approach. Investors are able to perform an effective evaluation to assist in allocating investment funds, and the government bodies can implement supplement housing policy in response to the public needs.