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Completing Right-of-Way (ROW) acquisition process on schedule is critical to avoid delays and cost overruns on transportation projects. However, transportation agencies face challenges in accurately forecasting ROW acquisition timelines in the early stage of projects due to complex nature of acquisition process and limited design information. There is a need of improving accuracy of estimating ROW acquisition duration during the early phase of project development and quantitatively identifying risk factors affecting the duration.

The quantitative research methodology used to develop the forecasting model includes an ensemble algorithm based on decision tree and adaptive boosting techniques. A dataset of Georgia Department of Transportation projects held from 2010 to 2019 is utilized to demonstrate building the forecasting model. Furthermore, sensitivity analysis is performed to identify critical drivers of ROW acquisition durations.

The forecasting model developed in this research achieves a high accuracy to predict ROW durations by explaining 74% of the variance in ROW acquisition durations using project features, which is outperforming single regression tree, multiple linear regression and support vector machine. Moreover, number of parcels, average cost estimation per parcel, length of projects, number of condemnations, number of relocations and type of work are found to be influential factors as drivers of ROW acquisition duration.

This research contributes to the state of knowledge in estimating ROW acquisition timeline through (1) developing a novel machine learning model to accurately estimate ROW acquisition timelines, and (2) identifying drivers (i.e. risk factors) of ROW acquisition durations. The findings of this research will provide transportation agencies with insights on how to improve practices in scheduling ROW acquisition process.

Prior research on meeting or beating earnings thresholds documents that firms with earnings momentum are awarded with valuation premiums. However, it is unclear from this strand of literature why this is the case. Therefore, this study aims to investigate the effects of time-varying earnings persistence on earnings momentum and their pricing effects.

This study exploits a firm that reports earnings momentum as research setting to examine whether earnings persistence is significantly higher for firms with consecutive earnings increases. In addition, it investigates a relation between earnings momentum and fundamentals-driven earnings persistence and estimates return associations of earnings momentum conditional on economic-based persistence of earnings.

The empirical evidence suggests that firms with earnings momentum reflect higher time-varying earnings persistence. It further reveals that longer duration of earnings momentum is associated with higher fundamentals-driven earnings persistence. More importantly, valuation premiums are exclusively assigned to earnings momentum determined by strong firm fundamentals, not momentum itself.

This study provides new empirical evidence that valuation premiums accrued to firms with earnings momentum are conditional on time-varying earnings persistence. The research implications are relevant to investors, regulators and auditors, as the results bring conclusions that earnings momentum reflects successful business models not poor accounting quality. This leads to a more complete view of earnings momentum and helps allocate resources when evaluating earnings-momentum firms.

Natural disasters profoundly influence agricultural trade sustainability. This study investigates the effects of natural disasters on agricultural production imports in China within 2002 and 2018. This exploration estimates the mediating role of transportation infrastructure and agriculture value-added and the moderating role of government effectiveness and diplomatic relations.

This investigation uses Probit, Logit, Cloglog and Ordinary Least Squares (OLS) models.

The results confirm the mediating role of transportation infrastructure and agriculture value-added and the moderating role of government effectiveness and diplomatic relations in China. According to the findings, natural disasters in trading partners heighten the risk to the agricultural imports. This risk raises, if disasters damage overall agricultural yield or transportation infrastructure. Moreover, governments’ effective response or diplomatic ties with China mitigate the risk. Finally, the effect of disasters varies by the developmental status of the country involved, with events in developed nations posing a greater risk to China’s imports than those in developing nations.

China should devise an early warning system to protect its agricultural imports by using advanced technologies such as data analytics, remote sensing and artificial intelligence. In addition, it can leverage this system by improving its collaboration with trading partners, involvement in international forums and agreement for mutual support in crisis.

Existing labor estimation models typically consider only certain construction project types or specific influencing factors. These models are focused on quantifying the total labor hours required, while the utilization rate of the labor during the project is not usually accounted for. This study aims to develop a novel machine learning model to predict the time series of labor resource utilization rate at the work package level.

More than 250 construction work packages collected over a two-year period are used to identify the main contributing factors affecting labor resource requirements. Also, a novel machine learning algorithm – Recurrent Neural Network (RNN) – is adopted to develop a forecasting model that can predict the utilization of labor resources over time.

This paper presents a robust machine learning approach for predicting labor resources’ utilization rates in construction projects based on the identified contributing factors. The machine learning approach is found to result in a reliable time series forecasting model that uses the RNN algorithm. The proposed model indicates the capability of machine learning algorithms in facilitating the traditional challenges in construction industry.

The findings point to the suitability of state-of-the-art machine learning techniques for developing predictive models to forecast the utilization rate of labor resources in construction projects, as well as for supporting project managers by providing forecasting tool for labor estimations at the work package level before detailed activity schedules have been generated. Accordingly, the proposed approach facilitates resource allocation and enables prioritization of available resources to enhance the overall performance of projects.

The purpose of this study is to determine the viability of Lacticaseibacillus rhamnosus GR-1 (L. rhamnosus GR-1) in five yogurt samples with or without quinoa, chickpea, soybean and rice flour over various fermentation periods and refrigerated storage durations, with a focus on exploring the potential of functional foods, which provide health benefits beyond nutritional value. Additionally, the study aimed to evaluate consumer acceptance of yogurt fortified with functional flour. Using a nine-point hedonic scale, from 1 (dislike extremely) to 9 (like extremely), participants rated appearance, flavour, texture and overall acceptability.

The samples were inoculated with the probiotic strain L. rhamnosus GR-1 and fermented for 0, 2, 4 and 6 h at 38°C, followed by refrigerated storage at 4°C for 1, 15 and 30 days, respectively. Microbial enumeration was performed throughout fermentation and storage to assess the viability of L. rhamnosus GR-1. A sensory evaluation involving 86 participants was conducted to assess the consumer acceptability of the yogurt samples.

Notably, L. rhamnosus GR-1 achieved viable counts of 108 colony-forming units per mL in all treatments at all fermentation time points. Over the 30-day storage period, no statistically significant differences (p < 0.05) in average pH values were observed among the five treatments, and within each treatment, pH levels remained stable, with an overall mean of 4.2 ± 0.64. Treatment 4, which featured rice flour fortification, received higher hedonic scores from sensory panellists in terms of appearance, flavour, texture and overall acceptability. These findings indicate that incorporating functional flours in conjunction with cow’s milk effectively promotes and preserves the viability of L. rhamnosus GR-1 in yogurt.

Exploring the potential of probiotic yogurt enriched with diverse functional flours to enhance nutritional content and health benefits as well as attract new consumers, this study addressed a critical gap in understanding consumer perceptions and generated insights for creating innovative and health-promoting dairy products.

The purpose of this study is to identify the relationship between collaborative innovation and the financial performance of information technology (IT) firms through the mediating role of strategic agility and absorptive capacity. Customer knowledge management capability (CKMC) is also explored as a potential moderator.

Data were collected from 300 respondents working in different small to medium IT enterprises operating in different cities around Portugal. The simple random sampling method was used for data collection, and Smart partial least squares-structural equation modeling (Smart PLS-SEM version 3.2.8) was used to test the hypotheses.

The findings demonstrate that collaborative innovation contributes significantly to the financial performance of IT firms in Portugal. The results also indicate that absorptive capacity and strategic agility both positively and significantly affect the relationship between collaborative innovation and firms’ financial performance. However, while the moderating role of CKMC has a positive and significant effect on the relation between collaborative innovation and strategic agility, CKMC insignificantly moderates the relation between collaborative innovation and absorptive capacity.

Few studies have explicitly connected collaborative innovation with firms’ financial performance; this study attempts to fill that gap. Moreover, this research investigates the mediating role of strategic agility and absorptive capacity in the relationship between collaborative innovation and financial performance. Finally, by discussing the moderating effect of CKMC, which leads to enhanced financial performance, this study proposes that when complex and unpredictable situations occur, managers should focus on customer-oriented strategies and innovation at the same time to outpace their competitors.

Although the prior literature has identified the relevance of dealer participation for multinational enterprises (MNEs), it is unclear whether such participation could also be an important means for local dealers to learn from MNEs. By adopting local firms’ viewpoint, our study draws on organizational learning theory to examine how local dealers benefit from their participation with foreign suppliers in Africa.

The empirical setting is a combinative dataset of secondary data and primary survey of 164 small- and medium-sized local dealers with nine subsidiaries of a Chinese motorcycle company in six countries of Sub-Saharan Africa.

This research shows that dealer participation is positively associated with dealer performance, and this positive effect is stronger when local dealers operate in regions with low government corruption and high government support. However, the positive relationship is weaker when local dealers use the local tongue extensively but becomes stronger when their foreign suppliers have a high dealer coverage.

By taking a local-participant perspective, our study extends the participation literature to show how firms from a resource-constrained region may benefit from their proactive participation with foreign counterparts. Additionally, we identify the boundary conditions of institutional factors and strategic choices of local dealers and foreign suppliers, providing a nuanced understanding of firm behaviors in complex and uncertain markets.

Existing literature shows conflicting views regarding street vendors in a place. They are considered both positive and negative. Their existence has rarely been examined from a combination of place-making and power theories. This research aimed (a) to identify the actors who transform Borobudur Food and Craft Market and the sources of power and actions carried out by these actors and (b) to find out the views of other actors about street vendors.

The design used in this study was an instrumental case study. The data were collected using semi-structured interviews and photo documentation. The sampling technique used was purposive sampling with several participants of as many as 12 persons consisting of 4 street vendors, 4 employees of the state-owned enterprise in charge of the Borobudur tourist site and 4 tourists. The data were analyzed through two-phased coding. To improve the credibility, participant validation was conducted.

This study made new findings. First, in a place, there are formal and informal place-making actors who transform the place with the sources of power they have and the acts of power they carry out. Both formal and informal actors can perform coercive and noncoercive acts of power. This shows the existence of contested power in a setting. Second, street vendors are viewed positively as well as negatively. Comprehensive policies need to be implemented by key actors to minimize the negative sides of the existence of street vendors and optimize the benefits from them.

Data collection was carried out when the Indonesian government implemented restrictions on public activities during the pandemic. At that time, tourism activities were very limited. In the future, researchers can use other techniques such as the self-report visual method because not all street vendors are fluent in expressing their opinions in interviews.

Both central and regional governments and local stakeholders can synergistically carry out a dialogue, seeking common ground to accommodate each other's interests. The next steps are to consistently apply the policies resulting from the dialogue and ensure that each actor plays a role according to their respective portion and authority.

Previous studies typically explain power as the possession of resources and relational attributes. This study has taken a different point of view, namely about acts of power contested in a certain place. Actors who have power are not always those who have formal legitimacy. Informal parties are considered powerless despite having power.

Pre-construction of a project comprises stages that are pivotal for the procurement performance. It is defined as the duration from the project's initiation to construction. However, Private Public Partnerships (PPPs) have been subjected to a long pre-construction, thereby leading to an inefficient development process. Therefore, the purpose of this paper is to pay attention to the influencing factors elongating the pre-construction duration.

Based on data of 5,677 PPP projects between 2009 and 2021 in China, the authors adopt the Accelerated Failure Time (AFT) model in duration analysis to empirically analyze the following underlying dynamics determining the duration of PPP pre-construction stages: (1) policy uncertainty; (2) corruption; and (3) procurement method selection. To observe the influencing paths more specifically, the authors divided the pre-construction duration into the pre-tendering period and tendering period and regressed them separately.

The results indicate that the pre-construction duration is significantly prolonged with increased policy uncertainty and corruption degree as well as the use of tendering methods. Meanwhile, the above factors have a greater impact on the pre-tendering period than the tendering period.

The contribution of this study is twofold: (1) theoretically, this paper provides new evidence on the impact of PPP policy uncertainty, corruption and procurement method selection on the pre-construction duration. It complements empirical studies on the factors elongating the time efficiency of PPPs projects. (2) In practice, it provides a specific path for the government to improve the time efficiency of PPPs.

Prior studies on the impact of incentives on physicians’ online participation mainly focused on different incentives while ignoring the difficulty of setting monetary incentives efficiently. Based on goal-setting theory, the current research examines the relationship between incentives with goals of varying difficulty and professional health knowledge sharing (PHKS) in online health knowledge-sharing platforms (OHKSPs).

Four field experiments with different monetary incentives were conducted by one of China’s largest OHKSPs, with whom the researchers cooperated in data collection. Monthly panel data on 10,584 physicians were collected from September 2018 to December 2019. There were 9,376 physicians in the treatment group and 1,208 in the control group. The authors used a difference-in-difference (DID) model to explore the research question based on the same control group and the Chow test with seemingly unrelated estimation (sureg) to compare regression coefficients between four groups. Several robustness checks were performed to validate the main results, including a relative time model, multiple falsification tests and a DID estimation using the propensity score matching method.

The results show that the monetary incentive significantly positively affected the volume of physicians’ PHKS directly with negative spillover to the duration of physicians’ PHKS. Moreover, the positive effect of incentives with higher difficulty on the volume of physicians’ PHKS was significantly smaller than that of incentives with low difficulty. Finally, professional title had a positive moderating effect on the volume of goal difficulty setting and did not significantly moderate the effect on the duration of physicians’ PHKS.

Some limitations of this study are: firstly, because the field experiments were enterprise benefit oriented, the treatment and control groups were not balanced. Secondly, the experiments for different incentive measures were relatively similar, making it challenging to validate a causal effect. Finally, more consideration should be given to the strategy for setting hierarchical incentives in future research.

The research indicates that monetary incentives have a bilateral effect on PHKS, i.e. a positive direct effect on the volume of physicians’ contributions and a negative spillover effect on the duration of physicians’ PHKS. The professional titles of physicians also moderate such bilateral switches of PHKS. Furthermore, when a physician’s energy is limited, the goal difficulty setting of the incentive mechanism tends to be low. The more difficult the incentives are, the more inefficient the effects on physicians’ PHKS will be.