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The big‐on‐asbestos (BOA) system is a mobile pipe‐external robotic crawler used to remotely strip and bag asbestos‐containing lagging and insulation materials (ACLIM) from various diameter pipes in (primarily) industrial installations. Steam and process lines within the Department of Energy (DoE) weapons complex warrant the use of a remote device due to the high labor costs and high level of radioactive contamination, making manual removal extremely costly and highly inefficient. Currently targeted facilities for demonstration and remediation are Fernald in Ohio and Oak Ridge in Tennessee.

This paper develops an organizing framework for research on corporate political strategy. It reviews the literature and then identifies a number of open research questions and streams for potential investigation. The paper closes by developing a theory to explain why, when, and how a firm will pursue multi-forum political action as part of its nonmarket and integrated strategy.

In order to replace the conventional human maintenance of cable‐stayed bridges, a robot is designed and constructed for tasks such as cleaning, painting and rust‐detecting.

Adopting a modular approach, two kinds of climbing mechanisms, plus a painting mechanism and a rust‐detecting method are designed.

A robot that can climb and maintain the cables of cable‐stayed bridges has been designed and constructed. It has been proved by experiment that the robot can overcome many disadvantages of conventional human bridge‐maintenance, and drastically improve efficiency, cost, and safety.

The robot is of industrial size, but a new mechanism requiring less installing time will be designed for the future.

The robot has been applied to cables of the Nanpu Bridge and Xupu Bridge in Shanghai. More than 80 cable‐stayed bridges and six suspension bridges have been built or are being constructed across large rivers in China alone. This gives an enormous potential market.

The cable maintenance robot developed in this paper is the world's first special robot for the cables of cable‐stayed bridges.

The purpose of this paper is to show how data analytics can be used to identify areas of potential cost savings for category managers of installation-level services. Using integrated solid waste management (ISWM) as a test case, the authors also examine the impact of small business set-asides on price and contractor performance.

The authors use data analytics, specifically sequential regression, the Wilcoxon rank-sum test and ordered logistic regression to investigate the influence of service- and contracting-related variables on price and contractor performance.

The authors find that service- and contracting-related variables influence price. Specifically, they identify that a service-related variable, number of containers, significantly affects price, and that two contracting-related variables, one type of small business set-aside and the number of offers received, also significantly affect price. The authors quantify the price premiums paid for using various types of small business set-asides.

Although the findings were significant, the authors believe that the robustness of the conclusions could be enhanced if the Air Force captured more data. Additional observations would increase the generalizability of the results.

This empirical experiment demonstrates that detailed analyses are required to gain insights into services’ price drivers to craft more appropriate category management strategies for installation-level services.

This empirical study shows how historical data can be used to assess price drivers of installation-level services. It is also one of the first to quantify the impact that small business set-asides have on price.

Purpose: Investors and portfolio managers can earn profitably when they correctly predict when stock prices will go up or down. For this reason, it is crucial to know the effect levels of the factors that affect stock prices. In addition to macroeconomic factors, the psychological behavior of investors also affects stock prices. Therefore, the study aims to reveal the different sensitivity levels of the stock index against macroeconomic and psychological factors.

Design/Methodology/Approach: In this study, dollar rate (USD), euro rate (EURO), time deposit interest rate (IR), gold price (GOLD), industrial production index (IPI), and consumer price index (CPI) (inflation (INF)) were used as macroeconomic factors, while Consumer Confidence Index (CCI) and VIX Fear Index (VIX) were used as psychological factors. In addition, the BIST-100 index, which is listed in Borsa Istanbul, was used as the stock index. The sensitivity of the stock index to macroeconomic and psychological factors was investigated using the Multivariate Adaptive Regression Spline (MARS) method using data from January 2012 to October 2020.

Findings: In the analyses performed using the MARS method, the coefficients of INF, USD, EURO, IR, CCI, and VIX Index were found to be statistically significant and effective on the stock index. Among these variables, INF has the highest effect on stocks. It is followed by USD, IR, EURO, CCI, and VIX. GOLD and IPI variables did not show statistical significance in the model. The most important difference of the MARS model from other regressions is that each factor’s effect on the stock index is analyzed by separating it according to the value of the factor. According to the results obtained from the MARS model: (1) it has been determined that USD, EURO, IR, and CPI have both positive and negative effects on the stock market index and (2) CCI and VIX have been found to have negative effects on stocks. These results provide essential information about how investors who plan to invest in the stock index should take into consideration different macroeconomic and psychological values.

Originality/value: This study contributes to the literature as it is one of the first studies to examine the effects of factors affecting the stock index by decomposing it according to the values it takes. Also, this study provides additional information by listing the factors affecting the stock index in order of importance. These results will help investors, portfolio managers, company executives, and policy-makers understand the stock markets.

Over half of the US states have jettisoned an exclusive focus on profit maximization for shareholders and created new corporate structures, called “benefit corporations”, which give equal standing to the achievement of social and environmental objectives. This paper aims to examine the factors leading to adoption of legislation for the business formation of benefit corporations by the US states.

Event History Analysis (EHA), a time-series technique using panel data of non-repeatable events, is used to identify and understand economic, political and diffusion factors that affect the adoption of benefit corporation enabling legislation in the US states.

The results strongly indicate that politics matters – states in which the Democratic Party or liberal ideology controls governmental functions are more likely to pass these laws. There is also evidence that states that are more innovative in their approach to policy-making are more likely to adopt these laws. Otherwise, unemployment, tax burden, political culture, enacted constituency statutes and geographic diffusion have no discernible relationship with the adoption of benefit corporation laws.

The paper provides warning signs to firms considering expending costly resources on the establishment of or conversion to benefit corporation status and the related investment in developing skills for the preparation, review and assurance of required annual benefit corporation reporting.

The findings suggest future adoption of benefit corporation enabling laws may slow considerably.

This study aims to analyzes the effects of the consumer-generated media (CGM) boom on hotel managers’ investment behavior concerning quality signals.

Survival analysis has been conducted, considering the permanence/dropout of the Spanish hotels in a quality certification system during the 1998–2020 period.

The number of hotels certified since 2010 has been progressively falling, pointing to a decreasing interest of the managers in these certifications. Nevertheless, this is not a generalized phenomenon: the hotel characteristics and the number and nature of reviews about them in CGM significantly affect their permanence decisions in certification systems.

The findings provide several keys to optimizing investment management in quality signals considering hotel characteristics and their positioning in CGM.

To the best of the authors’ knowledge, this is the first study that analyses the relationship between the presence of hotels in CGM and their investments in alternative quality signals. The results will allow future investment decisions based on previous real business experiences.

Regarding the premises of open innovation (OI) in terms of knowledge sources, this paper aims to discuss how to manage the existing sources of knowledge in supply chains.

An integrative review was developed focusing on studies related to supply chain and OI, seeking to understand the relationships between them, supporting the innovative discussion.

The SIPOC-OI was proposed as a tool to support the management of knowledge sources present in the supply chain, promoting efficiency to the company and improving its innovative capacity.

The conceptual proposal should be empirically verified to understand the management tool's obstacles and benefits for a company's innovation performance. Additionally, it would be useful to understand the results of this proposal in the relationships between agents of the chain, as well as the direction (inbound, outbound or coupled). Additionally, relevant points were highlighted as future agendas.

The point of view based on OI treats the collaboration's aspects and its benefits to agents, which becomes an essential factor in improving the entire chain's integration and performance.

The analysis of the flow of knowledge in supply chains from an OI perspective is an innovation in theory. Besides, the multidisciplinary proposal is expressed in the framework developed as it is based on a tool from engineering. Supply chain competencies/mindset is important to develop OI as well as is the contrary – there is a mutual practical and theoretical relevance between the integration of the concepts.

This study examines the direct and indirect effects of social capital on supply chain performance via supply chain quality integration (SCQI), which refers to integrating supply chain partners from the perspective of quality management. It also examines the moderating role of environmental uncertainty in the link between social capital and SCQI and determines the conditional indirect effect of social capital on supply chain performance via SCQI.

Data were collected using a time-lagged research design through a self-administered survey of supply chain professionals in manufacturing firms in Pakistan. Hayes’ PROCESS Macro was used to test the hypotheses.

The results show a positive relationship between social capital and supply chain performance. SCQI partially mediates the relationship between social capital and supply chain performance. Environmental uncertainty significantly moderates that relationship in such a way that firms that operate under high environmental uncertainty are more likely to use their social capital to develop SCQI than firms that operate under low environmental uncertainty.

The study has practical implications for managers who seek to implement SCQI practices using social capital. Leveraging social capital across the supply chain fosters strong connections and a quality-oriented approach across the supply chain, and improves overall performance. Managers can use the power of social capital to navigate environmental uncertainty.

This study’s originality lies in its drawing on the dynamic capability theory and contingency theory and integrating the dispersed scholarly work on social capital, SCQI, and supply chain performance under the boundary condition of environmental uncertainty.

This research investigates the impact of the strategic sourcing process on the supply chain response to COVID-19. The paper presents practitioners' perspectives (experts in supply chain management, especially involved in the procurement field) on the strategic sourcing process's impact on the supply chain response.

The study follows a survey-based approach for data collection. It uses a descriptive survey methodology where questions related to the impact of the strategic sourcing process on the supply chain response in the face of the coronavirus pandemic were explored by practitioners.

In total, 130 valid responses were obtained. The results showed that the majority of respondents agreed or strongly agreed that strategic sourcing positively impacts the supply chain response amid the COVID-19 effects. Also, for the five phases of the strategic sourcing process, the majority of respondents considered them as a high and very high impact on the supply chain response.

This paper provides timely insights for practitioners and academics, especially those involved in the supply chain management area, showing how the strategic sourcing process plays an important role in making supply chains more responsive amid disruption situations.

Findings of this paper clearly shows the impact of the phases of the strategic sourcing process on the responsiveness of the supply chains amid the COVID-19 pandemic. This can encourage supply chain leadership to devote more time to strategic sourcing initiatives to generate improvements on the supply chain performance.

This paper is unique since it brings an unexplored relation in respect to strategic sourcing amid disruption situations, such as the COVID-19 pandemic, from a practitioner's perspective. It also significantly contributes to developing new directions for the supply chain management domain to deal with large-scale disruptions, such as the coronavirus pandemic.