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The author develops a bilateral Nash bargaining model under value uncertainty and private/asymmetric information, combining ideas from axiomatic and strategic bargaining theory. The solution to the model leads organically to a two-tier stochastic frontier (2TSF) setup with intra-error dependence. The author presents two different statistical specifications to estimate the model, one that accounts for regressor endogeneity using copulas, the other able to identify separately the bargaining power from the private information effects at the individual level. An empirical application using a matched employer–employee data set (MEEDS) from Zambia and a second using another one from Ghana showcase the applied potential of the approach.

This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.

This paper aims to prevent gasket sealing failure in engineering, accurately predict gasket life, extend system life and improve sealing reliability. The accelerated life test method of flexible graphite composite–reinforced gaskets is established, the life distribution law of flexible graphite composite–reinforced gaskets is revealed, and the life prediction method of flexible graphite composite–reinforced gaskets with different allowable leakage rates is proposed, which can provide a reference for the life prediction of other types of gaskets.

In this study, flexible graphite composite–reinforced gaskets were tested for long-term high-temperature sealing performance on a multi-sample gasket accelerated life test rig. The data were also analyzed using the least squares method and the K-S hypothesis calibration method. A gasket time-dependent leakage model and an accelerated life model were also developed. Constant stress-accelerated life tests were conducted on flexible graphite composite–reinforced gaskets. On this basis, a gasket life prediction method at different allowable leakage rates was proposed.

The life distribution law of flexible graphite composite–reinforced gaskets is revealed. The results show that the life of the gasket obeys the Weibull distribution. The time-correlated leakage model and accelerated life model of the gasket were established. And the accelerated life test method of the flexible graphite composite–reinforced gasket was established. The life distribution parameters, accelerated life model parameters and life estimates of gaskets were obtained through tests. On this basis, a gasket life prediction method under different leakage rates was proposed, which can be used as a reference for other types of gaskets.

The research in this paper can better provide guidance for the use and replacement of gaskets in the project, which is also very meaningful for predicting the leakage condition of gaskets in the bolted flange connection system and taking corresponding control measures to reduce energy waste and pollution and ensure the safe operation of industrial equipment.

A multi-specimen gasket-accelerated life test device has been developed, and the design parameters of the device have reached the international advanced level. The life distribution law of the flexible graphite composite–reinforced gasket was revealed. The accelerated life test method for the flexible graphite composite–reinforced gasket was established. The life prediction method of the flexible graphite composite–reinforced gasket under different allowable leakage rates was proposed.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2023-0254/

This paper aims mainly at introducing applied statisticians and econometricians to the current research methodology with non-Euclidean data sets. Specifically, it provides the basis and rationale for statistics in Wasserstein space, where the metric on probability measures is taken as a Wasserstein metric arising from optimal transport theory.

The authors spell out the basis and rationale for using Wasserstein metrics on the data space of (random) probability measures.

In elaborating the new statistical analysis of non-Euclidean data sets, the paper illustrates the generalization of traditional aspects of statistical inference following Frechet's program.

Besides the elaboration of research methodology for a new data analysis, the paper discusses the applications of Wasserstein metrics to the robustness of financial risk measures.

This paper gives a model of collusion formation and a method of measuring the degree of it among the traders/bidders in the agricultural commodity markets in India. The important assumption is that the bidding is repetitive with a set of common bidders. The theory has been derived based on the behavior of the wholesale market of agricultural commodities in India. The paper is based on full information in the collusion formation. The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data.

The paper used the standard theory of optimization and the theory of auction and probability statistics.

This is a complete information model of cartel formation. The bidding is repetitive and continues forever in discrete time. Hence bidders behavior is observable. Using the proposed method, if the APMC measures for each market and publishes on a periodic basis, say weekly basis, then it will be easier to break the collusion in the market where relative collision is present. For example, if a farmer has three options to sell in three different markets, then the published data would help them to select the market where the degree of collusion is relatively lower. Moreover, the undesirable loss can be avoided based on the right choice of market. As a result, transaction costs will be optima.

The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data.

The monetary policy implementation and corporate investment are closely intertwined. The aim of modern monetary policy is to mitigate economic fluctuations and stabilise economic growth. One of the ways of influencing the real economy is influencing the level of investment by enterprises.

This chapter provides evidence on how monetary policy affected corporate investment in Poland between 1Q 2000 and 3Q 2022. We investigate the impact of Polish monetary policy on investment outlays in contexts of high uncertainty.

Using the correlation analysis and the regression model, we show the relation between the monetary policy and the investment outlays of Polish enterprises. We used the least squares method as the most popular in linear model estimation. The evaluation includes model fit, independent variable significance and random component, i.e. constancy of variance, autocorrelation, alignment with normal distribution, along with Fisher–Snedecor test and Breusch–Pagan test.

We find that Polish enterprises are responsive to changes in monetary policy. Hence, the corporate investment level is correlated with the effects of monetary policy (especially with the decision on the central bank's basic interest rate changes). We found evidence that QE policy has a positive impact on Polish investment outlays. The corporate investment in Poland is positively affected by respective monetary policies through Narodowy Bank Polski (NBP) reference rate, inflation, corporate loans, weighted average interest rate on corporate loans.

Being an efficient mechanism for the value of money, public–private partnership (PPP) is one of the most prominent approaches for infrastructure construction. Hence, many controversies about the performance effectiveness of these delivery systems have been debated. This research aims to develop a novel performance management perspective by revealing the causal effect of key performance indicators (KPIs) on PPP infrastructures.

The literature review was used in this study to extract the PPPs KPIs. Experts’ judgment and interviews, as well as questionnaires, were designed to obtain data. Copula Bayesian network (CBN) has been selected to achieve the research purpose. CBN is one of the most potent tools in statistics for analyzing the causal relationship of different elements and considering their quantitive impact on each other. By utilizing this technique and using Python as one of the best programming languages, this research used machine learning methods, SHAP and XGBoost, to optimize the network.

The sensitivity analysis of the KPIs verified the causation importance in PPPs performance management. This study determined the causal structure of KPIs in PPP projects, assessed each indicator’s priority to performance, and found 7 of them as a critical cluster to optimize the network. These KPIs include innovation for financing, feasibility study, macro-environment impact, appropriate financing option, risk identification, allocation, sharing, and transfer, finance infrastructure, and compliance with the legal and regulatory framework.

Identifying the most scenic indicators helps the private sector to allocate the limited resources more rationally and concentrate on the most influential parts of the project. It also provides the KPIs’ critical cluster that should be controlled and monitored closely by PPP project managers. Additionally, the public sector can evaluate the performance of the private sector more accurately. Finally, this research provides a comprehensive causal insight into the PPPs’ performance management that can be used to develop management systems in future research.

For the first time, this research proposes a model to determine the causal structure of KPIs in PPPs and indicate the importance of this insight. The developed innovative model identifies the KPIs’ behavior and takes a non-linear approach based on CBN and machine learning methods while providing valuable information for construction and performance managers to allocate resources more efficiently.

This paper aims to disentangle the mechanism linking digital servitization and manufacturing firm performance. The contributions of the service networks and slack resources are analyzed.

Drawing on a survey of manufacturing firms that have implemented or are implementing digital service projects in China, this paper examines the mediation effect of service networks and the moderated mediation effect of slack resources to capture the role of service networks and slack resources in the relationship between digital servitization and manufacturing firm performance.

Both basic and advanced digital services can equally contribute to manufacturing firm performance. Service networks mediate the relationship between basic digital servitization and manufacturing firm performance. No moderated mediation effect of slack resources is found, but slack resources negatively moderate the effects of basic digital services on service networks and positively impact service networks.

The mediating mechanism of service networks in the relationship between digital servitization and manufacturing firm performance is theorized, and it is clarified that service networks mediate the association between basic digital services and manufacturing firm performance but not advanced digital services. Additionally, there is no significant difference in performance implications when manufacturing firms provide basic versus advanced digital services, answering the call for research on the various types of digital servitization. This paper also identifies firms’ slack resources as the boundary conditions under which basic digital services influence service networks and the positive impacts of slack resources on service networks, bridging the network literature, organizational slack literature and digitalization literature under the framework of service ecosystem research.

This paper aims to investigate the links between daily review sentiment and the hotel performance measures of occupancy rate (OR), average daily rate (ADR) and revenue per available room (RevPAR).

The authors conducted review sentiment analyses in three moments (−1, −7 and −14 days) before arrival time using a data set of budget hotel performance and online reviews. The aim was to identify the effect of review sentiment in the budget hotel market on the three performance metrics.

Daily sentiment positively affects ADR and negatively affects OR and RevPAR, but only up to a certain threshold, after which the trend reverses. Prices increase with the level of sentiment, and high prices lead to low OR and RevPAR only when the sentiment scores are low. When they are high, they are associated with low rates, which lead to high OR and RevPAR.

Daily review sentiment can be viewed as a valuable “barometer” indicating a hotel’s daily operational effectiveness. Daily sentiment can thus allow hotel managers to adjust their dynamic pricing strategies more accurately.

This study identifies daily sentiment as an alternative predictor of hotel performance. In addition to the roles of valence and volume in the decision-making process, the authors found that daily review sentiment can be an “in-the-moment” factor with a high impact, encouraging consumers to complete their transactions. This study suggests that aggregated measures such as the total number of reviews and overall ratings of the hotel should not be the sole consideration in reputation management.

The purpose of the study is to investigate how small- and medium-sized enterprises (SMEs) can effectively collaborate for eco-innovation using the business modes of innovation framework to emphasise three types of collaboration: “science, technology, and innovation” (STI), “learning by doing, using, and interacting” (DUI)-Vertical and DUI-Horizontal.

This analysis uses data from 838 SMEs in the Basque Country (2018–2020) to evaluate the effects of the three types of collaboration on eco-innovation. The authors employ a propensity score-based method to address potential bias associated with endogeneity in innovation studies.

The findings suggest that DUI-Vertical collaboration has a positive relationship with the development of product, process and marketing eco-innovation. Furthermore, DUI-horizontal collaboration is the most effective collaboration mode for SMEs, positively impacting their overall eco-innovation portfolio. Finally, STI collaboration is positively associated with product eco-innovation.

Policymakers should support SMEs by designing programmes that facilitate collaboration between competing firms to stimulate eco-innovation, but potential challenges of coopetition must be addressed. Rather than a generic, one-size-fit-all approach, SMEs' managers should identify the most appropriate partners corresponding to their specific eco-innovation goal, ensuring a more effective and targeted. Collaboration between science partners and SMEs should be reinforced by approximating the SMEs' needs more effectively.

This study contributes twofold. Firstly, the authors investigate whether the STI and DUI modes of innovation are determinant factors in the introduction of various types of eco-innovation. Secondly, the authors contribute to the literature on business modes of innovation by differentiating between DUI-Vertical (i.e. suppliers, customers and consultancy) and DUI-Horizontal (i.e. competitors) collaboration, thus highlighting the complexity of DUI collaboration forms.