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The purpose of this paper is to assess alternative economic explanations of buildings’ height in Latin America and Chile, inductively producing a theory about skyscrapers’ height in emerging countries. In the quest for height, global exposure as advertising guides developers located in emerging economies, while ego-building for investors.

This paper uses mixed methods triangulation (MMT). Findings with small sample econometrics for 38 cities from 13 different countries are re-interpreted by linguistically analyzing 11 semi-structured interviews with local experts in Santiago.

Globalization is the main determinant of skyscrapers height in the Latin American region, its interaction with the need to portray management and technical skills of developer firms, determines a process toward over-construction.

Because of small sample bias, the quantitative results are not fully reliable, but this is precisely why it makes sense to use MMT.

Santiago offers a valuable case study because, on the one hand, Chile was the first Latin American country to undertake neoliberal type reforms, as early as 1973. On the other, the tallest Latin American skyscraper is to be completed in this city by 2015. The theory developed, derived from the evidence and the perceptions, has a Global South reach and can open-up an empirical research agenda.

This paper innovates in real estate research by using MMT, not just to confirm quantitative findings, but as an inductive theory building tool. It also analyses Latin America, a region with scarce presence in the literature.

This paper aims to build a set of long-term, geographically controlled land value indices for Santiago de Chile, with which to test land rent theory predictions regarding macroeconomic impacts.

This paper uses a geographic cluster approach to the Laspeyres estimator, weighted by the stock of available land plots and their market offers per zone, to create two quarterly land value indices for Gran Santiago during the period 1983Q4–2016Q2. Subsequently, this paper implements dynamic time series methods (Vector Error Correction) as a baseline to determine the effect of economic performance and interest rate on urban land values.

The two land value indices are correctly predicted by economic and interest rate shocks, as theoretically expected. In addition, this paper found that land values grew faster-than-predicted during the period of the so-called “Chilean Miracle” (1992–1998), a situation associated in the literature with worsened housing affordability and socio-spatial inequality.

The land value indices offer unprecedented time-series precision in tracking the long-term performance of real estate markets in a Latin American city, allowing us to produce short- and long-term (accumulative) time-series causality analyses.

This study aims to test the effect of Seattle’s discontinuous sidewalk requirement, on the number of housing units per construction permit.

This study uses discontinuity linear regression (DLR) on a database of Seattle’s housing construction permits during January-2015 to January-2018, controlled by 51 socioeconomic, planning and geographic variables. The sidewalk requirement is continuous inside the designated urban villages; however, it is spatially and quantitatively discontinuous in the rest of the city: certain blocks at certain locations require sidewalks’ design and construction in permits with six or more housing units. DLR detects the effect of the discontinuity while controlling for a vast array of confounding variables.

The primary finding is that the discontinuous requirement reduces the number of housing units in about 75% of a housing unit per permit, which at the aggregate level amounts to around 335 fewer housing units during the period of analysis.

The database is relatively small, which has limited a more thorough specification process and robustness tests.

Besides directly testing the effect of a discontinuous in-kind development contribution, the research setup allows to discuss a wider, more structural problem: the possibility of contributions avoidance due to spatial substitution. In contrast, spatially continuous (i.e. city-level) contributions cannot be avoided by performing spatial substitution, and they are internalized by the housing supply side (market-neutral).

This paper argues that decentralization reforms in Colombia, implemented since the 1980s, have led to the decentralization of political clientelism rather than its demise. Clientelism is a system of political and economic institutions that turns every local democracy into an extractive political institution. The authors theoretically demonstrate that an increase in public resources will increase corruption.

The authors develop and test a subnational public choice model, where clientelism in elections and corruption in public administration constitute a stable long-term institutional equilibrium. The model comprises two linked subgames: electoral tournament and corruption in public policy. The model makes two predictions that currently oppose predominant approaches: (1) increasing the severity of jail sentences to electoral crimes increases their price and the predominance of machine politics, instead of improving the quality of electoral tournaments and (2) increasing local governments' public finance increases clientelism in elections and corruption in public administration.

The authors find evidence in favor of the theoretical model of curse of public resources, using difference-in-differences estimation with a database 2016–17 of Colombia's 1,034 municipalities. This country is well-suited for our analysis because it has a long-term commitment to formal democratic processes (since 1958), while plagued by endemic corruption and clientelism problems.

(1) The theoretical approach is innovative and disruptive of current models on the problem, (2) the model builds upon the Colombian situation, a country with prominent corruption and political violence problems regardless of its relatively long-term commitment with free elections (since 1958) and (3) the theoretical discussion is tested using a comprehensive set of difference-in-differences estimations.

The purpose of this quantitative study was to investigate Penn State Extension 4-H volunteer leaders’ leadership development needs and preferred delivery methods for leadership development. The participants were 147 volunteer leaders who attended Penn State Extension Annual 4-H Leader Forum and filled out the survey. We found that the overall mean score for leadership skills needs among volunteer leaders was 4.33 (SD =.45). Volunteers’ overall leadership skills needs do not differ based on volunteer gender, level of education, age, and previous volunteer experience. The preferred delivery methods of leadership development for Penn State Extension 4-H volunteer leaders were workshop and in-service training. Leadership education is critical in advancing volunteers’ skills and preparing them to delivery well-developed, state of the art contemporary leadership education programs.

This study aims to determine whether, by means of the application of genetic algorithms (GA) through the traditional technical analysis (TA) using moving average convergence/divergence (MACD), is possible to achieve higher yields than those that would be obtained using technical analysis investment strategies following a traditional approach (TA) and the buy and hold (B&H) strategy.

The study was carried out based on the daily price records of the NASDAQ financial asset during 2013–2017. TA approach was carried out under graphical analysis applying the standard MACD. GA approach took place by chromosome encoding, fitness evaluation and genetic operators. Traditional genetic operators (i.e. crossover and mutation) were adopted as based on the chromosome customization and fitness evaluation. The chromosome encoding stage used MACD to represent the genes of each chromosome to encode the parameters of MACD in a chromosome. For each chromosome, buy and sell indexes of the strategy were considered. Fitness evaluation served to defining the evaluation strategy of the chromosomes in the population according to the fitness function using the returns gained in each chromosome.

The paper provides empirical-theoretical insights about the effectiveness of GA to overcome the investment strategies based on MACD and B&H by achieving 5 and 11% higher returns per year, respectively. GA-based approach was additionally capable of improving the return-to-risk ratio of the investment.

Limitations deal with the fact that the study was carried out on US markets conditions and data which hamper its application in some extend to markets with not as much development.

The findings suggest that not only skilled but also amateur investors may opt for investment strategies based on GA aiming at refining profitable financial signals to their advantage.

This paper looks at machine learning as an up-to-date tool with great potential for increasing effectiveness in profits when applied into TA investment approaches using MACD in well-developed stock markets.

In the Industry 4.0 (I4.0) era, small and medium enterprises (SMEs) face significant pressure to make their manufacturing operations more sustainable. However, SMEs often lack the knowledge and information needed to leverage I4.0 technologies for achieving sustainability. This paper aims to develop a multi-criteria decision-making (MCDM) model to prioritize sustainability functions supported by I4.0 technologies in SMEs.

The fuzzy-DEMATEL method was developed to classify sustainability functions based on their prominence and influence, categorizing them into cause-and-effect groups. Experts in I4.0 technologies, sustainability and SMEs from Brazil were consulted during the data collection phase. Sensitivity analysis was also performed to validate the results obtained through the DEMATEL method.

The results indicate that the most prominent and influential sustainability functions include organizing production processes, employee skill development and simplifying production planning and control. Therefore, investing in I4.0 technologies to support these functions can enable SMEs to amplify the impact of their sustainability initiatives and improve operational efficiency. The authors also observed that improving quality monitoring is the primary function within the effect group.

This paper serves as a roadmap for SME managers seeking to enhance the effectiveness of their sustainability practices using I4.0 technologies, thereby maximizing impact while minimizing the complexity of implementation.

This study ranks key sustainability functions as actions and practices that SMEs can implement using I4.0 technologies to achieve sustainability. It also identifies the most prominent and influential functions managers should prioritize when investing in I4.0 technologies.

Looks at how immigration in the USA has changed so that by the late 1980s almost three‐quarters of a million legal immigrants were entering the country ever year, and how by the 1980s this had increased to 9 million! Investigates the changing birthrate by which foreign born residents now account for one in five births in the USA. Posits that Islam is the fastest growing religion and that the USA has metamorphosed from being a “Christian” country to be the most religiously diverse nation in the world.

The provision of Industry 4.0 solutions demands a vast range of technology domains. To provide these solutions, small and medium-sized enterprises (SMEs) may need the support of different supply chain actors through an inbound open innovation strategy. The authors study the contribution of four types of supply chain actors for inbound open innovation: suppliers, competitors with complementary technologies, R&D centers and customers. The authors analyze how these four actors moderate the effect of integrated Industry 4.0 solutions on three main competitive strategies: cost, focalization and differentiation.

The authors conducted a survey on 77 SMEs from the automation sector, using OLS regression with moderating effects. They considered the integration of 15 technologies and 7 classic automation activities in the provision of Industry 4.0 solutions. The authors also studied three competitive outputs – technology cost reduction (cost), customer loyalty (focalization) and technology innovation (differentiation) – as well as four supply chain actors (moderators).

Expanding the provision of Industry 4.0 technologies increases customer loyalty and technology innovation. Collaboration with competitors (complementary technologies) leverage these results and reduce technology costs. Integration between customers and R&D centers elevates costs but R&D centers can foster long-run innovation.

This study is the first to empirically investigate inbound open innovation in the supply chain for technology development in the context of Industry 4.0. The authors discuss how these actors contribute to four inbound open innovation activities: technology scouting; horizontal technology collaboration; vertical technology collaboration; and technology sourcing.

The logistics industry has undergone a tremendous transformation. This transformation is necessary to cope with the fundamental changes in customer expectations and the need for digitalization imposed by the pandemic, changes in the socioeconomic world, and innovative technology solutions. This paper aims to present digital transformation as an integrated framework for transforming the operating model and applying advanced solutions to the ecosystem of a quintile logistics (5PL) company. 5PL operators are typically an ecosystem. Loosely coupled or self-organized entities that collaborate in a symbiotic relationship represent this ecosystem. They aim to jointly develop capabilities, create innovative services or solutions, share knowledge, facilitate transactions, and leverage network synergies in a logistics environment to provide optimized or novel customer- or partner-centric solutions (Lamberjohann and Otto, 2020).

Currently, there is no single definition of an integrated logistics operations model in 5PL practice, so the qualitative method used in this paper allows for investigation from an exploratory perspective. The paper follows a qualitative research methodology, collecting and analyzing data/facts through interviews and visits to subject matter experts, industry practitioners, and academic researchers, combined with an extensive review of academic publications, industry reports, and written and media content from established organizations in the marketplace. This paper follows a qualitative research methodology, as it is an inquiry rather than a statistical study. The qualitative method allows the study of the concepts of phenomena and definitions, their characteristics, and the defining features that serve as the basis (Berg, 2007). It emphasizes generalized interpretation and deeper understanding of concepts, which would be more difficult in quantitative, statistically based research. Fact-finding was conducted in two ways: in-depth interviews with experts from academia, information and communication technology organizations, and key players in the logistics industry; and academic publications, industry reports, and written and media content from established national and international organizations in the market.

The operations model introduced considers six aspects: persons, processes, platforms, partners, protection and preservation. A virtual team approach can support the personal side of the 5PL ecosystem’s digital transformation. Managing a 5PL ecosystem should be based on collaborative planning, forecasting, and replenishment methods (Parsa et al., 2020). A digital platform can support trust among the stakeholders in the ecosystem. A blockchain solution can powerfully support the 5PL ecosystem from partner relationships’ points of view. The implementation of a cybersecurity reference model is important for protection (Bandari, 2023). Reverse logistics and an integrated approach support the preservation of the ecosystem.

While the author has experience applying the different components of the operations model presented, it would be interesting to find a 5PL that would use all the components presented in an integrated way. The operations model presented applies to any similar ecosystem with minor adaptations.

This paper addresses operations models and digital transformation challenges for optimizing 5PL operators. It provides several opportunities and considerations for 5PL operators interested in improving their management and operations to cope with the growing challenges of today’s world.

The competitiveness and long-term performance of 5PL operators depend on selecting and carefully implementing their operations models. This paper emphasizes the importance of using advanced operations models.

The operations model derives from the author’s personal experiences in research and the innovative application of these models to logistics operators (DHL, UPS, Poste Italiane and others). This paper brings together academic and industry perspectives and operations models in an integrated business digital transformation. This paper defines an original optimal operations model for a 5PL operator and can add sustainable value to organizations and society. In doing so, it outlines different solution requirements, the critical success factors and the challenges for solutions and brings logistical performance objectives when implementing a digital business transformation.