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Hiring managers commonly rely on system-justifying motives and attitudes during résumé screening. Given the prevalent use of modern résumé formats (e.g. LinkedIn) that include not only an applicant's credentials but also headshot photographs, visible sources of information such as an applicant's race are also revealed while a hiring manager simultaneously evaluates a candidate's suitability. As a result, such screening is likely to activate evaluation bias. The purpose of this paper is to examine the role of a hiring manager's perceptions of race-system justification, that is, support for the status quo in relations between Black and White job candidates in reinforcing or mitigating hiring bias related to in-group and out-group membership during résumé screening.

Drawing from system justification theory (SJT) in a pre-selection context, in an experimental study involving 174 human resource managers, the authors tested two boundary conditions of the expected relationship between hiring manager and job candidate race on candidate ratings: (1) a hiring manager's affirmative action (AA) attitudes and system-justifying attitudes and (2) a job candidate's manipulated suitability for a position. This approach enabled us to juxtapose the racial composition of hiring manager–job candidate dyads under conditions in which the job candidate's race and competency for a posted position were manipulated to examine the conditions under which White and Black hiring managers are likely to make biased evaluations. The authors largely replicated these findings in two follow-up studies with 261 students and 361 online raters.

The authors found that information on a candidate's objective suitability for a job resulted in opposite-race positive bias among Black evaluators and same-race positive bias among White evaluators in study 1 alone. Conversely, positive attitudes toward AA policies resulted in in-group favoritism and strengthened a positive same-race bias for Black evaluators (study 1 and 2). We replicated this finding with a third sample to directly test system-justifying attitudes (study 3). The way in which White raters rated White candidates reflected the same attitudes against systems (AA attitudes) that Black raters rating Black candidates exhibited in the authors’ first two studies. Positive system-justifying attitudes or positive attitudes toward AA did not, however, translate into the elevation of same-race candidate ratings of suitability above those of opposite-race candidates.

Although the size of the sample is on par with the percentage of Blacks nationwide in private-sector managerial-level positions ideally, the authors would have preferred to oversample Black HR managers. Given the scarcity of focus on Black HR managers, future researchers, using diverse samples of evaluators should also consider not only managers' and candidates' race but also their social dominance orientation. Moreover, it is important that future researchers use more racially diverse samples from other industries to more fully identify the ways in which the dynamics of system-justifying processes can emerge to influence evaluation bias during résumé screening.

Advances in technology pose new challenges to HR hiring practices. This study attempts to fill a void regarding the unintended effects of bias during digital résumé screening. These trends have important HR implications. Initial screening of a job applicant's credentials while concurrently viewing the individual's photograph is likely to activate subconscious evaluation bias, produces inaccurate applicant ratings. This study's findings should caution hiring managers about the potential for bias to arise when viewing job candidates' digital résumés and encourage them to carefully examine various boundary conditions on racial similarity bias effects on applicant pre-screening and subsequent hiring decisions.

The study’s results suggest that bias might be attenuated as organizational leaders engage in efforts to understand their system-justifying motives and examine perceptions of the workplace social hierarchy (i.e. responses to status hierarchies) linked to perceptions of the status quo. For example, understanding how system justifying motives influence evaluation bias will inform how best to design training and other interventions that link discussions of workforce diversity to the relationships among groups within the organization's social hierarchy. This line of research should be further explored to better understand the complex forces at work when hiring managers adopt system-justifying motives during hiring evaluations.

The authors address the limitations of prior research by examining interactions between boundary conditions in a real-world context using real human resources hiring managers and more contemporary personnel-screening practices to test changes in the direction and strength of the relationship between hiring manager–job candidate race and hiring manager evaluations. Thus, the authors’ findings have implications for hiring bias and understanding of system-justification processes, particularly regarding how, when and why hiring managers support the status quo (i.e. perpetuate inequity) even if they are disadvantaged as a result.

The purpose of this paper is to explain two new FINRA rules: Rule 2090 (Know Your Customer) and Rule 2111 (Suitability).

The paper explains the two rules, the expanded requirements in the new suitability rule, and an expansion in the list of factors an associated person is required to consider as part of a customer's investment profile before making a recommendation.

FINRA's new suitability rule is notable for three reasons: the revised rule covers investment strategies and explicit recommendations to hold securities; it expands the necessary factors for making a suitability determination; and it includes definitions for three specific suitability evaluations.

Prior to the effective dates of the new rules, most likely in the Fall of 2011, firms may want to consider whether to develop additional procedures to gather customer “investment profile” information and whether to memorialize that information in written form.

This paper provides practical guidance from experienced financial services lawyers.

Crop suitability analysis is vital for identifying a piece of land’s potential for sustainable crop production and aids in the formulation of an effective agricultural management plan. This study aims to conduct crop suitability analysis of prominent Kharif (rice and maize) and Rabi (potato and wheat) crops in Sirajganj district, a flood-prone area of Bangladesh, and recommend a suitable cropping pattern to mitigate the detrimental effects of flooding.

Various factors such as soil drainage, soil depth, soil moisture, soil texture, soil permeability, soil pH, erosion hazard, nutrient status and flooding risk were considered for this study. For all four crops, the weights of each factor were determined using the analytical hierarchy process approach, and the scores of each subfactor were assigned on the basis of favorable circumstances of crop cultivation. Using the weighted overlay analysis in the ArcGIS 10.3 environment, the crop suitability maps were generated and were divided into four suitable classes. Geographic information system integration of crop suitability for all the crops determined the suitable cropping pattern of the study area in Kharif and Rabi seasons.

A vast portion of the study area covering 64.80% of the total land is suitable for cultivating either rice or maize in Kharif season followed by either potato or wheat in Rabi season. Other suitable cropping pattern for Kharif and Rabi seasons found in the study area are rice-wheat, rice-wheat/potato, rice/maize-wheat and rice/maize-potato, which covers a little portion of the study area.

This research validates the suitable location of crop cultivation on the basis of flooding occurrences in the locality.

Blockchain and distributed ledger technologies are increasingly prominent, yet their adoption remains complex. This paper addresses the common misalignment between blockchain technology and actual needs, often leading to project failure. It introduces a decision-making framework focused on the technological aspects of blockchain adoption.

We designed the framework by analyzing key decision drivers from existing literature and applied it to a real-world use case in the electric vehicle supply chain. The blockchain solution was tested with live production data.

Blockchain is beneficial for use cases requiring decentralized governance, but it often needs to be supplemented with additional technologies in industrial applications.

The framework provides a set of managerial-level questions that simplify the decision-making process for those without deep technical expertise, helping determine when blockchain is appropriate, valuable and superior to other technologies.

Following the methodology designed for selecting the best industrial and technological diversification strategy, one of the best methods for achieving the long-term sustainability of companies, the purpose of this paper is to describe its application in the service supply chains (SSCs) sector, specifically, in freight transport in product service supply chains.

The methodology used in diversification processes comprises four stages: evaluation of the technological diversification suitability; selection of the technological diversification strategy; implementation of the diversification strategy; and evaluation of the process.

The main contributions of the paper are: the proposal of a taxonomy or functional inventory for information and communication technologies (ICTs) in the freight transport industry (FTI); the introduction of a new concept, the technological shrub, a variant of the technological tree that allows interdependencies between the functionality systems; the construction of a technological shrub for ICTs in a standard FTI firm; and the multicriteria selection, based on the Analytic Hierarchy Process (AHP), of the best diversification strategy that can be incorporated by this standard firm for improving competitiveness. This selection utilises a “bottom-up” approach.

The paper deals with the long-term sustainability of companies by means of technological diversification strategies. Based on the taxonomy constructed for ICTs in the SSC sector and the identification of key technologies for a particular firm, a technological shrub is constructed and a multicriteria procedure is developed in order to select the best diversification strategy.

The purpose of this paper is to establish a maturity evaluation model for the application of construction steel structure welding robotics suitable for the actual situation and specific characteristics of engineering projects in China and then to assess the maturity level of the technology in the application of domestic engineering projects more scientifically.

The research follows a qualitative and quantitative analysis method. In the first stage, the structure of the maturity model is constructed and the evaluation index system is designed by using the ideas of the capability maturity model and WSR methodology for reference. In the second stage, the design of the evaluation process and the selection of evaluation methods (analytic hierarchy process method, multi-level gray comprehensive evaluation method). In the third stage, the data are collected and organized (preparation of questionnaires, distribution of questionnaires, questionnaire collection). In the fourth stage, the established maturity evaluation model is used to analyze the data.

The evaluation model established by using multi-level gray theory can effectively transform various complex indicators into an intuitive maturity level or score status. The conclusion shows that the application maturity of building steel structure welding robot technology in this project is at the development level as a whole. The maturity levels of “WuLi – ShiLi – RenLi” are respectively: development level, development level, between starting level and development level. Comparison of maturity evaluation values of five important factors (from high to low): environmental factors, technical factors, management factors, benefit factors, personnel and group factors.

In this paper, based on the existing research related to construction steel structure welding robot technology, a quantitative and holistic evaluation of the application of construction steel structure welding robot technology in domestic engineering projects is conducted for the first time from a project perspective by designing a maturity evaluation index system and establishing a maturity evaluation model. This research will help the project team to evaluate the application level (maturity) of the welding robot in the actual project, identify the shortcomings and defects of the application of this technology, then improve the weak links pertinently, and finally realize the gradual improvement of the overall application level of welding robot technology for building steel structure.

This study was concerned with relationships between selected candidate characteristics and both candidates' immediate reactions to interviews and interviewers' evaluations of them. Candidates' self‐reported academic performance was unrelated to their immediate reactions to interviews. Candidates whose academic performance was poor were judged to be weak candidates by interviewers. Interviewers also saw these candidates as less intelligent. Candidates who came from working class background were more highly motivated to succeed and also tended to be more anxious before interviews. However, social class background was unrelated to interviewer judgments. There were a number of relationships between candidates' recollections of their affective responses during past interviews and their immediate reactions to the interviews studied here. Compared with other candidates, those who had disliked being interviewed in the past were more anxious and less confident about their interviews and also liked interviewers less personally. These negative affective responses were also associated with poor evaluations from interviewers.

China is a large country with different regions due to regional differences and project characteristics, and the selection of prefabricated building technology according to local conditions is the key to its sustainable development in China. The purpose of this paper is to develop the suitability evaluation system of prefabricated building technology from the perspective of the suitability concept and to analyze the selection path of prefabricated building technology and to provide a reference for selecting and developing prefabricated building technology schemes that meet regional endowments.

Based on relevant literature, technical specifications, and standards, this paper constructs an index system for analyzing the technical suitability of prefabricated buildings. It includes 23 indicators, 7 dimensions, and 3 aspects through the semantic clustering method. Following this, the comprehensive weight of each index is determined using the order relation method (G1) and the continuous ordered weighted averaging (COWA). The selection of technical schemes is comprehensively evaluated using Visekriterjumska Optimizacija Ikompromisno Resenje (VIKOR) and Fuzzy Comprehensive Evaluation Method.

 (1) The technical suitability of prefabricated buildings is influenced by 7 core factors, such as adaptability of resources and environment, project planning and design level, and economic benefit; (2) When selecting the appropriate technology for prefabricated buildings, economic suitability should be considered first, followed by regional suitability, and then technical characteristic; (3) The prefabricated building technology suitability evaluation model constructed in this paper has high feasibility in the technical suitability selection of the example project.

The comprehensive evaluation model of prefabricated building technology suitability constructed in this paper provides technical selection support for the promotion and development of prefabricated buildings in different regions. In addition, the model can also be widely used in areas related to prefabricated building consulting and decision-making, and provides theoretical support for subsequent research.

This study provides a new decision support tool for prefabricated building technology suitability selection, which helps decision makers to make more rational technology choices.

This study has a positive impact on the advancement of prefabricated building technology, the improvement of construction industry standards, and the promotion of sustainable development.

The contribution of this study is twofold: (1) Theoretically, this paper provides technical evaluation indicators and guidelines for provincial and regional governments to cultivate model cities, plan industrial bases, etc. (2) In practice, it offers project-level appropriate technology system solutions for the technology application of assemblers in various regions.

Modular integrated construction (MiC) is a modern construction method innovating and reinventing the traditional site-based construction method. As it integrates advanced manufacturing principles and requires offsite production of volumetric building components, several factors and conditions must converge to make the MiC method suitable and efficient for building projects in each context. This paper aims to present a knowledge-based decision support system (KB-DSS) for assessing a project’s suitability for the MiC method.

The KB-DSS uses 21 significant suitability decision-making factors identified through literature review, consultation of experts and questionnaire surveys. It has a knowledge base, a DSS and a user interface. The knowledge base comprises IF-THEN production rules to compute the MiC suitability score with the efficient use of the powerful reasoning and explanation capabilities of DSS.

The tool receives the inputs of a decision-maker, computes the MiC suitability score for a given project and generates recommendations based on the score. Three real-world projects in Hong Kong are used to demonstrate the applicability of the tool for solving the MiC suitability assessment problem.

This study established the complex and competing significant conditions and factors determining the suitability of the MiC method for construction projects. It developed a unique tool combining the capabilities of expert systems and decision support system to address the complex problem of assessing the suitability of the MiC method for construction projects in a high-density metropolis.

Policy makers are frequently challenged by the need to achieve sustainable development in cities and regions. Current decision-making processes are based on evaluation support systems which are unable to tackle the problem as they cannot take a holistic approach or a full account of actors. The purpose of this paper is to present a new generation of evaluation systems to support decision making in planning and regeneration processes which involve expert participation. These systems ensure network representation of the issues involved and visualization of multiple scenarios.

A literature review is used for both revising existing evaluation tools in urban planning and the built environment and highlighting the need to give stakeholders (industry, cities, operators, etc.) new tools for collaborative or individual decisions and to facilitate scaling up solutions. An overview of the new generation of decision support systems, named Multicriteria Spatial Decision Support Systems (MC-SDSS) is provided and real case studies are analyzed to show their ability to tackle the problem.

Recent research findings highlight that decisions in urban planning should be supported by collaborative and inclusive processes. Otherwise, they will fail. The case studies illustrated in this study highlight the usefulness of MC-SDSS for the successful resolution of complex problems, thanks to the visualization facilities and a network representation of the scenarios.

The case studies are limited to the Italian context.

These SDSS are able to empower planners and decision makers to better understand the interaction between city design, social preferences, economic issues and policy incentives. Therefore, they have been employed in several case studies related to territorial planning and regeneration processes.

This study provides three case studies and a review of the new MC-SDSS methodology which involve the Analytic Network Process technique to support decision-making in urban and regional planning.