bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effectiveness of non-farm diversification on rural household income – evidence and policy implications from India
Authors: Kapoor Shreya , Kapoor Sanjeev 
Published: August 2021

PurposeDoubling farming households’ income through occupational diversification to the non-farm sector has been advocated to be of paramount importance in an agrarian economy such as India. The purpose of this paper is to analyse the effects of non-farm activities on rural household incomes in four different Indian states by using a propensity score matching technique and developing an endogenous switching model.Design/methodology/approachThe research is based on secondary data taken from four quinquennial rounds of employment and unemployment surveys conducted by the National Sample Survey Organization.FindingsThe matching results indicate a maximum monthly rise in per capita income of Rs. 60 in Gujarat and a minimum increase of Rs. 18 in Rajasthan among rural households employed in the non-farm sector as compared to the farm sector. The findings confirm that rural non-farm structural diversification cannot be viewed as a blueprint for increasing rural household incomes in different states. Further, it suggests the need to segmenting the different states on the basis of agricultural development for increasing rural incomes.Research limitations/implicationsThe study argues that Indian states with a strongly developed farm sector i.e. Gujarat and Punjab are not ideally suited to undergo structural changes in their economic pursuit. The estimates suggest that the transition of rural households from farm to non-farm-sector activities is a very weak strategy in agriculturally developed states of Gujarat and Punjab, whereas non-farm diversification becomes a pivotal strategy for increasing rural household incomes in less agriculturally developed states such as Rajasthan and Uttar Pradesh. A contrasting point that arises from these evidence is that although diversification to the non-farm sector leads to higher income, but the resultant figures are very scanty.Originality/valueThe present study contributes to the existing literature by providing evidence and policy implications on rural non-farm diversification in India and its impact on the rural household income. The study can help the policymakers in framing policies aiming at increasing the income of the rural household through the structural transition of the rural economy.
Measuring the housing sector’s contribution to GDP in emerging market countries
Authors: Acolin Arthur , Hoek-Smit Marja , Green Richard K. 
Published: August 2021

Purpose
This paper aims to document the economic importance of the housing sector, as measured by its contribution to gross domestic product (GDP), which is not fully recognized. In response to the joint economic and health crises caused by the COVID-19 pandemic, there is an opportunity for emerging market countries to develop and implement inclusive housing strategies that stimulate the economy and improve community health outcomes. However, so far housing does not feature prominently in the recovery plans of many emerging market countries.

Design/methodology/approach
This paper uses national account data and informal housing estimates for 11 emerging market economies to estimate the contribution of housing investments and housing services to the GDP of these countries.

Findings
This paper finds that the combined contribution of housing investments and housing services represents between 6.9% and 18.5% of GDP, averaging 13.1% in the countries with information about both. This puts the housing sector roughly on par with other key sectors such as manufacturing. In addition, if the informal housing sector is undercounted in the official national account figures used in this analysis by 50% or 100%, for example, then the true averages of housing investments and housing services’ contribution to GDP would increase to 14.3% or 16.1% of GDP, respectively.

Research limitations/implications
Further efforts to improve data collection about housing investments and consumption, particularly imputed rent for owner occupiers and informal activity require national government to conduct regular household and housing surveys. Researcher can help make these surveys more robust and leverage new data sources such as scraped housing price and rent data to complement traditional surveys. Better data are needed in order to capture housing contribution to the economy.

Practical implications
The size of the housing sector and its impact in terms of employment and community resilience indicate the potential of inclusive housing investments to both serve short-term economic stimulus and increase long-term community resilience.

Originality/value
The role of housing in the economy is often limited to housing investment, despite the importance of housing services and well-documented methodologies to include them. This analysis highlights the importance of housing to the economy of emerging market countries (in addition to all the non-GDP related impact of housing on welfare) and indicate data limitation that need to be addressed to further strengthen the case for focusing on housing as part of economic recovery plans.
Sales transformation: conceptual domain and dimensions
Authors: Corsaro Daniela , Maggioni Isabella 
Published: August 2021

Purpose
This study aims to offer a conceptualization of sales transformation, a phenomenon that is redefining the role of salespeople and the nature of Business-to-Business (B2B) relationships while disrupting the selling logics across a variety of industries.

Design/methodology/approach
Through a two-stage approach, the authors propose and test a conceptual model of sales transformation. The authors conducted 20 interviews and two focus groups with sales directors and managers. The authors then surveyed directors, executives and managers in the sales area (n = 190) and tested a reflective–formative hierarchical model using partial least squares structural equation modeling (PLS-SEM).

Findings
Sales transformation is a multidimensional construct that includes four higher-order dimensions, namely, people, digitalization, integration and acceleration, and 16 sub-dimensions. These dimensions simultaneously contribute to the sales transformation phenomenon that is conceptualized as a systemic process. This study also offers a measurement tool to assess the degree of sales transformation and enhance the value generated through sales.

Originality/value
Although many companies are facing challenges stemming from the process of sales transformation, most studies have only focused on micro-aspects of this transformation. This study provides a holistic view of sales transformation aimed at understanding the complexity of this phenomenon by adopting a macro-level perspective on the different dimensions that contribute to its occurrence and development.
The government spending multiplier in Latin American countries: does the institutional environment matter?
Authors: Acevedo Rafael , Mora Jose U. , Young Andrew T. 
Published: August 2021

PurposeMora and Acevedo (2019) report that the government spending multipliers in Latin American countries are notably higher than what is typically reported for developed economies. Latin American countries have been inclined toward using procyclical fiscal policies. Those policies have been perceived as being effective at mitigating the effects of the 2008–2009 Great Recession. This study aims to estimate the government spending multiplier using Latin American panel data from 19 Latin American countries from 2000 to 2018. The estimates are conditional on the extent of openness, capital mobility and economic freedom. Based on the results, the latter is important: the less economically free a country, the larger its spending multiplier. Lower economic freedom in Latin American countries can help to account for their large spending multipliers. In particular, restrictions on international trade are positively associated with multipliers. This is the case even while controlling the trade share of GDP.

Design/methodology/approachThe authors provide regression results that are conditional on the extent of openness, capital mobility and economic freedom.

FindingsThe less economically free a country, the larger its spending multiplier. Lower economic freedom in Latin American countries can help to account for their large spending multipliers. In particular, restrictions on international trade are positively associated with multipliers. This is the case even while controlling the trade share of GDP.

Originality/valueTo the best of the authors’ knowledge, this is first study to estimate the fiscal multiplier conditional on economic freedom levels. The authors provide correctly calculated multipliers conditional on different levels of economic freedom. The authors point the way to future studies considering the effectiveness of fiscal policy conditional on institutional/policy quality.
A methodology for managing public spaces to increase access to essential goods and services by vulnerable populations during the COVID-19 pandemic
Authors: Regal Ludowieg Andrés , Ortega Claudio , Bronfman Andrés , Rodriguez Serra Michelle , Chong Mario 
Published: August 2021

PurposeThe purpose of this paper is to present a spatial decision support system (SDSS) to be used by the local authorities of a city in the planning and response phase of a disaster. The SDSS focuses on the management of public spaces as a resource to increase a vulnerable population’s accessibility to essential goods and services. Using a web-based platform, the SDSS would support data-driven decisions, especially for cases such as the COVID-19 pandemic which requires special care in quarantine situations (which imply walking access instead of by other means of transport).Design/methodology/approachThis paper proposes a methodology to create a web-SDSS to manage public spaces in the planning and response phase of a disaster to increase the access to essential goods and services. Using a regular polygon grid, a city is partitioned into spatial units that aggregate spatial data from open and proprietary sources. The polygon grid is then used to compute accessibility, vulnerability and population density indicators using spatial analysis. Finally, a facility location problem is formulated and solved to provide decision-makers with an adaptive selection of public spaces given their indicators of choice.FindingsThe design and implementation of the methodology resulted in a granular representation of the city of Lima, Peru, in terms of population density, accessibility and vulnerability. Using these indicators, the SDSS was deployed as a web application that allowed decision-makers to explore different solutions to a facility location model within their districts, as well as visualizing the indicators computed for the hexagons that covered the district’s area. By performing tests with different local authorities, improvements were suggested to support a more general set of decisions and the key indicators to use in the SDSS were determined.Originality/valueThis paper, following the literature gap, is the first of its kind that presents an SDSS focused on increasing access to essential goods and services using public spaces and has had a successful response from local authorities with different backgrounds regarding the integration into their decision-making process.
Mining Arabic Twitter conversations on health care: a new approach to analysing Arabic language on social media
Authors: Alqtati Nael , Wilson Jonathan A.J. , De Silva Varuna 
Published: August 2021

Purpose
This paper aims to equip professionals and researchers in the fields of advertising, branding, public relations, marketing communications, social media analytics and marketing with a simple, effective and dynamic means of evaluating consumer behavioural sentiments and engagement through Arabic language and script, in vivo.

Design/methodology/approach
Using quantitative and qualitative situational linguistic analyses of Classical Arabic, found in Quranic and religious texts scripts; Modern Standard Arabic, which is commonly used in formal Arabic channels; and dialectical Arabic, which varies hugely from one Arabic country to another: this study analyses rich marketing and consumer messages (tweets) – as a basis for developing an Arabic language social media methodological tool.

Findings
Despite the popularity of Arabic language communication on social media platforms across geographies, currently, comprehensive language processing toolkits for analysing Arabic social media conversations have limitations and require further development. Furthermore, due to its unique morphology, developing text understanding capabilities specific to the Arabic language poses challenges.

Practical implications
This study demonstrates the application and effectiveness of the proposed methodology on a random sample of Twitter data from Arabic-speaking regions. Furthermore, as Arabic is the language of Islam, the study is of particular importance to Islamic and Muslim geographies, markets and marketing.

Social implications
The findings suggest that the proposed methodology has a wider potential beyond the data set and health-care sector analysed, and therefore, can be applied to further markets, social media platforms and consumer segments.

Originality/value
To remedy these gaps, this study presents a new methodology and analytical approach to investigating Arabic language social media conversations, which brings together a multidisciplinary knowledge of technology, data science and marketing communications.
Designing an uncertain bi-objective green leagile capacitated lot sizing problem considering FM/M/C queue system
Authors: Rabbani Masoud , Aghamohamadi Bosjin Soroush , Manavizadeh Neda , Farrokhi-Asl Hamed 
Published: August 2021

Purpose
This paper aims to present a novel bi-objective mathematical model for a production-inventory system under uncertainty.

Design/methodology/approach
This paper addresses agile and lean manufacturing concepts alongside with green production methods to design an integrated capacitated lot sizing problem (CLSP). From a methodological perspective, the problem is solved in three phases. In the first step, an FM/M/C queuing system is used to minimize the number of customers waited to receive their orders. In the second step, an effective approach is applied to deal with the fuzzy bi-objective model and finally, a hybrid metaheuristic algorithm is used to solve the problem.

Findings
Some numerical test problems and sensitivity analyzes are conducted to measure the efficiency of the proposed model and the solution method. The results validate the model and the performance of the solution method compared to Gams results in small size test problems and prove the superiority of the hybrid algorithm in comparison with the other well-known metaheuristic algorithms in large size test problems.

Originality/value
This paper presents a novel bi-objective mathematical model for a CLSP under uncertainty. The proposed model is conducted on a practical case and several sensitivity analysis are conducted to assess the behavior of the model. Using a queue system, this problem aims to reduce the items waited in the queue to receive service. Two objective functions are considered to maximize the profit and minimize the negative environmental effects. In this regard, the second objective function aims to reduce the amount of emitted carbon.
Effects of CEO and COO overconfidence on the firm's inventory leanness
Authors: Kim Bowon , Na Jaeseog 
Published: August 2021

PurposeThis study examines whether the behavioral attributes, such as overconfidence, of chief executive officers (CEO) and chief operating officers (COO) affect firm's inventory leanness. If they do, how are they interacting with each other? Moreover, incorporating market competition into the analysis, this study explores how the competition moderates the relationship between managerial overconfidence and inventory leanness.Design/methodology/approachUsing a large panel data of US manufacturing firms between 1998 and 2015, this study measures top managers' overconfident characteristics using stock option information. Then, a panel regression analysis is adopted to test the effects of managerial overconfidence on inventory leanness. Moreover, a moderation model is applied to investigate the interaction effects of market competition.FindingsFirms with overconfident COOs (CEOs), other circumstances being equal, increase (decrease) the inventory leanness as the market becomes more competitive.Practical implicationsThe study suggests that firms should understand top managers' behavioral characteristics to manage inventory efficiently. Collectively, CEOs (COOs) tend to increase (decrease) inventory levels due to their overconfidence as the market gets competitive. Firms should establish a systematic process to be reviewed by diverse stakeholders to deal with managerial overconfidence.Originality/valueThis study is an exploratory study that examines whether and how top management's behavioral attribute relates to a firm's operations performance. It underlines that CEO and COO's overconfident characteristics determine the inventory leanness when market competition is considered. Numerous studies on firm-level strategies emphasized the top managers' overconfidence as a key factor. However, behavioral characteristics at the top management level have rarely been studied in operations management fields. Based on the results, scholars could compare and understand the effects of CEO and COO overconfidence to provide insights into inventory management.
Network well-being from a balanced centricity perspective
Authors: Groven Fabian , Odekerken-Schröder Gaby , Zwakhalen Sandra , Hamers Jan 
Published: August 2021

Purpose
This paper aims to explore how tensions and alignments between different actors’ needs in a transformative services network affect balanced centricity, which is an indicator of well-being. Balanced centricity describes a situation in which all network actors’ interests and needs are fulfilled simultaneously. In such cases, all actors are better off, which increases both individual actors’ and overall actor-network well-being.

Design/methodology/approach
The empirical study takes place in nursing homes in which in-bed baths represent co-created service encounters that affect the well-being of focal actors (i.e. patients), frontline service employees (i.e. nurses) and transformative service mediators (i.e. family members), who have potentially competing needs. Using a qualitative, phenomenological approach, the study inductively explores and deductively categorizes actors’ personal experiences to gain deep, holistic insights into the service network and its complex web of actor interdependencies.

Findings
The resulting conceptual model of balanced centricity identifies actors’ lower-order needs as different manifestations of the psychological needs for autonomy, competence and relatedness. If actors’ needs are aligned, their psychological needs can be satisfied, which facilitates balanced centricity. If actors exhibit competing needs though, balanced centricity is impeded.

Practical implications
This study establishes actors’ psychological needs as the origin of tensions/alignments in multi-actor networks that impede/contribute to balanced centricity. Transformative service providers should try to address all actors’ psychological needs when co-creating services to achieve network well-being.

Originality/value
This study adopts a novel, multi-actor perspective and thereby presents a conceptual model that contributes to the understanding of balanced centricity. Future research could test this model in other transformative service settings.
The role of dynamic capability on a business model in knowledge-intensive firms
Authors: Bonyadi Naeini Ali , Jalilian Ahmadkalaei Seyedeh Hoda 
Published: August 2021

PurposeThe purpose of this paper is to identify the dynamic capabilities (DCs) affecting the business models (BMs) in knowledge-intensive firms (KIFs). This paper also examines how much these DCs affect the BMs.Design/methodology/approachThe research methodology included examining a research framework based on a literature review followed by a survey of KIFs. A sample of 214 KIFs was obtained and structured equation modeling analysis using two-stage partial least squares–artificial neural network approach was conducted to test the proposed hypotheses.FindingsThis study shows that managerial, innovation, intellectual capital, information technology, integration and knowledge-based DCs influence the BM in KIFs. The results indicate that “the human development” aspect of managerial DC has the most significant impact on the BM efficiency, and innovation DC has the greatest influence on BM innovation.Practical implicationsIdentifying DCs affecting the BM in KIFs provides practical results for managers and researchers in KIFs.Originality/valueThe present research uses for the first time a PLS–ANN approach in identifying the affecting DCs the BM in KIFs; examines its impact on the efficiency and innovation aspects of the BM; and enriches the literature on DCs and the BM, especially in the field of KIF.
Adaptations to first-tier suppliers’ relational anti-slavery capabilities
Authors: Emberson Caroline , Pinheiro Silvia Maria , Trautrims Alexander 
Published: August 2021

Purpose
The purpose of this paper is to examine how first-tier suppliers in multi-tier supply chains adapt their vertical and horizontal relationships to reduce the risk of slavery-like practices.

Design/methodology/approach
Using Archer’s morphogenetic theory as an analytical lens, this paper presents case analyses adduced from primary and secondary data related to the development of relational anti-slavery supply capabilities in Brazilian–UK beef and timber supply chains.

Findings
Four distinct types of adaptation were found among first-tier suppliers: horizontal systemisation, vertical systemisation, horizontal transformation and vertical differentiation.

Research limitations/implications
This study draws attention to the socially situated nature of corporate action, moving beyond the rationalistic discourse that underpins existing research studies of multi-tier, socially sustainable, supply chain management. Cross-sector comparison highlights sub-country and intra-sectoral differences in both institutional setting and the approaches and outcomes of individual corporate actors’ initiatives. Sustainable supply chain management theorists would do well to seek out those institutional entrepreneurs who actively reshape the institutional conditions within which they find themselves situated.

Practical implications
Practitioners may benefit from adopting a structured approach to the analysis of the necessary or contingent complementarities between their, primarily economic, objectives and the social sustainability goals of other, potential, organizational partners.

Social implications
A range of interventions that may serve to reduce the risk of slavery-like practices in global commodity chains are presented.

Originality/value
This paper presents a novel analysis of qualitative empirical data and extends understanding of the agential role played by first-tier suppliers in global, multi-tier, commodity, supply chains.