Search results

Contractors of different scales, operating in different construction industries of varying institutional and economic settings, have different considerations when making bid or no-bid and mark-up decisions. Focusing on the large and medium-sized contractors in the Jilin province, China, the purpose of this study is to examine important factors affecting their decision to bid (d2b) and mark-up decisions and investigate differences between large and medium-sized contractors in evaluating the importance of the various factors affecting their d2b and mark-up decisions.

This study used a survey design for timely data collection from a large population. Contractors’ bidding attitudes was collected using an online survey questionnaire with a list of 40 key factors. Statistical analytical methods were applied for comparing the two groups of contractors.

The results of this study indicate that factors related to client conditions are most critical for both large and medium-sized contractors in their d2b and mark-up decisions. The results also show statistically significant differences between the two groups of contractors on a subset of factors affecting their d2b and mark-up decisions. The large contractors have placed more emphasis on projects' potential financial and strategic benefits. Another notable finding is that both groups of contractors have placed great emphasise on “government legislations” in their d2b and mark-up decisions.

These findings should be interpreted in consideration of several limitations. Firstly, the sample size is relatively small, and the focus was on a single province in the China construction industry. Next, this study only explores differences between large and medium-sized contractors in evaluating the importance of the various factors affecting their d2b and mark-up decisions.

Contractors could refer list of critical factors in competing for jobs in Jilin province or other provinces of similar institutional and economic settings. Construction clients, on the other hand, should consider the list of critical factors in the formulation of their competitive tendering procedures, thus enhancing the efficiency in their procurement of construction services.

Research on contractors’ bidding decision-making in the context of Chinese construction industry remains scarce; the research findings have implications for the industry stakeholders.

This study aims to investigate clients' attributes, their key decision variables and causal relationships between the decision variables. In addition, the purpose of the study is to map-out from these analyses, the attributes of project clients that motivate contractors' bid decision.

A total of 50 responses were obtained from a questionnaire survey. 50% of participants are contractors. 44% are claims consultants, whilst 6% are manufacturers and clients. Beyond measures of central tendencies, analysis focussed on causal relationships by way of correlation, analysis of variance and reductionism.

All 20 factors considered have significant correlations with at least one other factor. Findings also show the factors can be clustered into six: reputation, financial strength, relationship with the bidder, organisational attributes, history with project attributes and project organisation.

Evidence suggests stakeholders have often struggled to consider the many decision factors reported in normative literature, numbering hundreds. By clustering the factors into sub-themes, bid decisioning has been made more efficient. The study also explains how client attributes could determine project success and contractor participation. Different stakeholders can use findings of this study for training and further studies.

Previous studies have considered bid decisioning indexically – factors were long, analyses were largely inconclusive, and causal relationships are orthogonal. Findings in this study have shown depth: 20 originating client-specific factors were clustered into six sub-themes, and correlations were established. The methodology used for the study is confirmatory and conclusive.

Insufficient time allocation for the bidding period occurs, causing drawbacks to both parties, the client and the bidder. Hence, this study aims to evaluate the time allocated for preparing a bid proposal as per the National Competitive Bidding (NCB) in the Sri Lankan context.

The study has adopted a mixed method approach and expert interviews and document review to detect, analyse and validate the issues, and solutions based on NCB along with the adequacy of the allocated bidding period used as main data collection tools. Both qualitative and quantitative data were analysed through manual content analysis and inferential analysis respectively.

Overall, 24 local issues with the existing competitive bidding process and solutions for each were identified. Among the 24 local issues, it was unanimously agreed by all interviewees that three specific issues require attention and improvement. These issues are related to the standard and incompleteness of bidding documents, inaccurate BOQ quantities measured by the consultant or the main contractor, and the excessive number of bidding document amendments by the consultant. It was revealed that a maximum of 42 calendar days (6 weeks) is sufficient for the bidding process while a minimum of 21 calendar days (3 weeks) is insufficient.

The findings of this study would be recommended that Information and Communication Technology Agency (ICTA) understand the necessity of revising the NCB reference to the time allocated for the preparation of bids. By recognising the importance of sufficient time allocation for bid preparation, this research serves as a practical guide for authorities involved in policy formulation, aiding them in implementing revisions that align with the dynamic requirements of bidding procedures.

This study aims to solve optimal pricing and power bidding strategy problem for integrated combined heat and power (CHP) system by using a modified heuristic optimization algorithm.

In electricity markets, generation companies compete according to their bidding parameters; therefore, optimal pricing and bidding strategy are solved. Recently, CHP units are significantly operated by generation companies to meet power and heat, simultaneously.

For validation, it is shown that profit is improved by 0.04%–48.02% for single and 0.02%–31.30% for double-sided auctions. As heat price curve is extracted, the simulation results show that when CHP system is integrated with other units results in profit increase and emission decrease by 3.04%–3.18% and 2.23%–4.13%, respectively. Also, CHP units significantly affect bidding parameters.

The novelties are pricing and bidding strategy of integrated CHP system is solved; local heat selling is considered in pricing and bidding strategy problem and heat price curve is extracted; the effects of CHP utilization on bidding parameters are investigated; a modified heuristic and deterministic optimization algorithm is presented.

This study aims to examine the reaction of anchor investors (AIs) to pre-IPO earnings management (EM). The authors use the unique detailed bid data from the Indian anchor experiment. The authors also study the reputed AIs’ EM detection ability and pricing behavior in response to pre-IPO EM.

The authors use unique AI bid data for 169 Indian IPO firms. Utilizing the logistic regression and Tobit regression models with industry and year-fixed effects, the authors examine the relationship between various measures of AI participation and proxies of short-term and long-term discretionary accruals.

The authors document that pre-IPO EM is positively associated with the likelihood of anchor backing but negatively related to the likelihood of reputed anchor backing. The findings indicate that AIs are misled by pre-IPO EM, but reputed AIs are not. The authors also observe that reputed AIs, compared to the non-reputed, pay less than the upper band with increasing EM. The findings are robust to using various AI measures and EM proxies.

The findings have significant implications for regulators in the implementation of AI concept in non-anchor markets and better implementation of policies in existing anchor settings. Findings can also be relevant for non-institutional investors in the IPO domain.

This is one of the few studies on institutional investors' IPO bidding behavior in response to pre-IPO EM. However, this is the first study to analyze AIs' IPO bidding behavior in response to pre-IPO EM.

Skewed pricing is a typical tactic used by tenderers in unit price projects to gain additional advantages at the expense of the owner or other competing tenderers. This paper aims to describe the development of a model for detecting skewed pricing in competitive tendering for unit price contracts.

The model evaluates how much the offered unit rates for work items deviate from the reasonable rate identified from the item’s submitted unit rates. Item rate deviations are integrated into a total deviation score for each submitted tender based on the relative weight of the work item to the total project amount. The model allows for assigning higher weights to work items that are more prone to skewed pricing, such as those that are performed early and those that are expected to experience quantity fluctuations.

The paper presents a detection model that uses only the submitted prices of the competing tenderers to perform the needed calculations, which reduces subjectivity in identifying skewed tenders. Two examples are given to demonstrate how the model may be used to detect skewed tenders.

The model supports tendering officials in the challenging task of identifying skewed tenders, which is required by rules and regulations governing public procurement. The model’s ease of use is expected to make it more widely used as a decision-support tool during the tender evaluation stage of real-world projects.

This study evaluates the effect of transparency measures on public procurement efficiency, focusing on Thailand’s Infrastructure Transparency Initiative (CoST). This study aims to understand its impact on the country’s public infrastructure procurement practices.

This paper analyses Thailand’s government construction procurement data, focusing on budgetary savings and CoST process participation. Budgetary savings are this study dependent variable, while the main intervention variable is the adoption of the CoST data disclosure standard. This study uses multiple linear regression, fixed-effects model and propensity score matching with the logit model for a comprehensive analysis.

This study shows that using the CoST data disclosure leads to notable budget savings in Thai public construction procurement. With CoST’s introduction, the savings rose by Baht 9.6m, and even with added controls, the savings remained significant at around Baht 3.3m. The savings consistently stay near 5% across different models. The propensity score matching method confirms these results, consistent with factors such as open bidding and agency categorisation.

This study might not capture all benefits, especially non-financial ones. Thailand’s unique context and potential biases in data sources also need consideration.

CoST evidence backs Thailand’s procurement transparency. This study recommends broadening CoST, streamlining online platforms and promoting digital public engagement. Training stakeholders and partnering with state-owned enterprises and local agencies is vital to align with CoST and mitigate risks.

This study shows a clear link between transparency from information disclosure and budget efficiency in public procurement, using data from Thailand. It highlights the potential of transparency measures in developing countries.

In industrial buyer–supplier relationships, being an attractive customer has been found to result in superior supplier performance. However, there is a limited understanding of how these benefits transfer to the public domain. This study aims to explore the influence of customer attractiveness on supplier resource mobilization efforts toward the public sector.

A qualitative approach was used, focusing on in-depth interviews with 23 informants from 3 critical and complex supplier markets. The data were processed using inductive coding and thematic analysis.

The findings indicate that customer attractiveness in the public sector influences suppliers’ mobilization efforts on several dimensions. In addition to stimulating competition in the tender phase, customer attractiveness can yield important benefits to quality, supply stability and innovation during the business relationship. It appears imperative for the public sector to improve its standings with suppliers to both mitigate the apparent risk of sub-par treatment and to unlock the preferential supplier treatment associated with being an attractive customer.

Receiving increased mobilization from suppliers will result in better use of public money and help improve resilience and innovation in public procurement.

This study extends the research on customer attractiveness in the public sector by being the first to explore the range and nature of its influence on supplier mobilization efforts.

This study aims to investigate the dynamic influences of clustered barriers that hinder electronic procurement technology (EPT) implementation in construction procurement, using the neuro-fuzzy system.

A comprehensive literature review was conducted and 21 barriers to EPT implementation within construction projects were identified. Based on an expert survey, 121 datasets were gathered for this study. Using mean and normalization analysis for the datasets, 15 out of the 21 barriers were deemed to have critical influences in EPT barriers phenomenon. Subsequently, the critical barriers were classified into five groups: human-related; technological risk-related; government-related; industry growth-related; and financial-related. The relationships and influence patterns between the groups of barriers to EPT implementation were analyzed using the neuro-fuzzy system. Furthermore, sensitivity analysis was performed to examine the dynamic influence levels of the barriers within the hindrance level composition.

The results reveal that addressing one barrier group does not reduce the high levels of hindrances experienced in EPT implementation. However, addressing at least two barrier groups mostly tends to reduce the hindrance levels for EPT implementation. Further, this study revealed that addressing some barrier group pairings, such as technological risk-related and government-related barriers, while other barrier groups remained at a high level, still resulted in high levels of hindrances to EPT implementation in construction procurement.

This study provides insights for researchers to help them contribute to the development of theory with contemporary approaches based on the influence patterns of barrier interrelationships.

This study provides a model that would help practitioners and decision makers in construction procurement to understand and effectively determine the complex and dynamic influences of barrier groups to EPT uptake, for the development of suitable mitigation strategies.

This study provides novel insights into the complex influence patterns among grouped barriers concerning EPT adoption in the construction industry. Researchers and practitioners are equipped with knowledge on the influence patterns of barriers. This knowledge aids the development of effective strategies that mitigate the combined groups of barriers, and promote the wider implementation of EPT in the construction industry.

After completion of the case study, the students would be able to comprehend the crisis at hand for Milkbasket, why did it resist Reliance’s takeover in the first place, then to evaluate the pros-cons and future prospects for the organization post-acquisition; to evaluate from an ethical standpoint the process of mergers and acquisitions using ethical frameworks to understand how, when, to whom and through what processes do mergers and acquisitions qualify the test of being ethical; and to analyse different hostile takeovers, especially through tender offers, proxy contests and toehold bidding strategy in this case.

Founded in 2015, Milkbasket was a micro-delivery start-up based in Gurugram (near New Delhi), India. Milkbasket would let its subscribers order till midnight and deliver groceries, milk and other everyday essentials to its subscribers before 7 a.m. next day. It had burnt a lot of cash and was facing difficulty in getting investors; as such they were engaged in discussions with many companies. Two of them – Reliance Retail Venture Limited and BigBasket – were not accepting the proposed valuation, but Milkbasket got term sheets from other two companies.

This case study can be used for graduate courses on strategic management, business ethics and corporate governance. This case study can also be used in corporate finance course to highlight the importance of making ethical/responsible judgements to protect stakeholder interests.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.