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This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

Adolescent pregnancy stands as a societal challenge, compelling young individuals to prematurely discontinue their education. Conversely, an expansion of high school education can potentially diminish rates of adolescent pregnancy, given that educational attainment stands as the foremost risk factor influencing sexual initiation, the use of contraceptive methods during initial sexual encounters and fertility. The aim of this paper is to analyze the impact of the implementation of the public educational policy introducing full-time schools (FTS) for high schools in the state of Ceará, Brazil, on early pregnancy rates.

Using the difference-in-differences method with multiple time periods, we measured the average effect of this staggered treatment on the treated municipalities.

The main result indicates a reduction of 0.849 percentage points in the teenage pregnancy rate. Concerning dynamic effects, the establishment of FTS in treated municipalities results in a 1.183–1.953 percentage point decrease in teenage pregnancy rates, depending on the timing of exposure. We explored heterogeneous effects within socioeconomically vulnerable municipalities, yet discerned no impact on this group. Rigorous tests confirm the robustness of the results.

This paper aims to contribute to: (1) the consolidation of research on the subject, given the absence of such research in Brazil to the best of our knowledge; (2) the advancement and analysis of evidence-based public policy and (3) the utilization of novel longitudinal data and methodology to evaluate adolescent pregnancy rates.

The purpose of this study is to explore the coopetition relationships between platform owners and complementors in complementary product markets. Drawing on the coopetition theory, the authors examined the evolutionary trends of the coopetition relationships between platform owners and complementors and explore the main influence factors.

The authors used Lotka–Volterra model to analyze the coopetition relationship between platform owners and complementors, including the evolutionary trends as well as the results. Considering the feasibility of sample data collection, simulation is used to verify the effects of different factors on the evolution of coopetition relationships.

The results show that there are four possible results of the competition in the complementary products market. That comprises “winner-take-all for platform owners,” “winner-take-all for complementors,” “stable competitive coexistence” and “unstable competitive coexistence,” where “stable competitive coexistence” is the optimal evolutionary state. Moreover, the results of competitive evolution are determined by innovation subjects’ interaction parameters. However, the natural growth rate, the initial market benefits of the two innovators and the overall benefits of the complementary product markets influence the time to reach a steady state.

The study provides new insights into the entry of platform owners into complementary markets, and the findings highlight the fact that in complementary product markets, platform owners and complementors should seek “competitive coexistence” rather than “winner-takes-all.” Moreover, the authors also enrich the coopetition theory by revealing the core factors that influence the evolution of coopetition relationships, which further enhance the analysis of the evolutionary process of coopetition relationships.

Not that long ago, half of all sales research was demonstrably if not unequivocally “atheoretical” (Williams and Plouffe, 2007). The foundational argument of this paper is that stronger theoretical development and application of theory in sales research is critical for the sales field to retain its relevancy. The purpose of this paper is to underscore that deliberate and cogent application of HWV (2018) is scant in the recent sales literature (over five years after publication in Journal of Marketing) for one or both of two reasons: scholars either do not understand the paper and/or are fearful of (mis)applying it.

More than simply introducing the articles to this special issue of the European Journal of Marketing (EJM), this paper also makes a number of important, overdue contributions. Although Hartmann, Wieland and Vargo’s JM (HWV, 2018) theoretical and conceptual paper has been well-received by the sales community, it has seen limited meaningful integration or application in sales research since its publication. This paper thus clarifies key misunderstandings and misperceptions with HWV (2018) so that sales researchers can more impactfully apply it to future sales research.

This paper identifies and then explains key aspects of service-dominant logic (S-D logic) and commonly misapplied and/or misunderstood aspects of HWV (2018) to guide future sales research. Ultimately, the overarching goal of this special issue of EJM is to focus a “spotlight” on sales theory development, while simultaneously demonstrating – through the five articles the special issue reports – that with purposeful effort, rich theoretical insights can effectively be applied to both “classic” and more current and emergent sales research topics.

Because HWV (2018) draw heavily upon S-D logic, it follows that some aspects of their article have been misinterpreted or misapplied by sales scholars. In particular, the critical concept of “crossing points” (both of the “thick” and “thin” variety) are explicated and detailed further, so as to afford sales researchers with better knowledge and insight on how to apply these key tools within HWV (2018).

The practical implications of this paper primarily revolve around further educating and clarifying for sales researchers “how” to better apply HWV (2018) to sales research, rather than simply citing it in passing. The paper also concludes by providing a summary and introduction to each of the five EJM special issue articles.

The originality and value of this paper and this special issue of the EJM is twofold. First, both this paper and the entire special issue itself emphasize the ongoing importance of advancing sales research through the meaningful and cogent application of theory. Second, the paper demonstrates that purposeful effort can lead to successful applications of HWV (2018) – as exhibited by the five articles in the EJM special issue – such that rich theoretical insights can be woven into both traditional and contemporary sales research topics.

This chapter provides an overview of Freire's primary approach to how governments control people, why governments dictate what is being taught and why they seek out control over educators. This chapter investigates the similarities Freire found between the most oppressive governments and dictatorships that rules by violence, to how our educational institutions are controlled. The stakes might be entirely different in these scenarios, but he knew the ultimate objective in all these situations was to remove power from the people, give it to a powerful few and ensure the people would never be able to regain control once more. These ideas and suggestions are key moving forward because it provides a baseline to understand how Freire thought about manipulative behaviours, and why tactics used in extremely violent situations can essentially be watered down and used to control people in universities in much the same way.

The article aims to establish whether the degree of aversion to inflation and the responsiveness to deviations from potential output have changed over time.

This paper assesses time variation in monetary policy rules by applying a time-varying parameter generalised methods of moments (TVP-GMM) framework.

Using monthly data until December 2022 for five inflation targeting countries (the UK, Canada, Australia, New Zealand, Sweden) and five countries with alternative monetary regimes (the US, Japan, Denmark, the Euro Area, Switzerland), we find that monetary policy has become more averse to inflation and more responsive to the output gap in both sets of countries over time. In particular, there has been a clear shift in inflation targeting countries towards a more hawkish stance on inflation since the adoption of this regime and a greater response to both inflation and the output gap in most countries after the global financial crisis, which indicates a stronger reliance on monetary rules to stabilise the economy in recent years. It also appears that inflation targeting countries pay greater attention to the exchange rate pass-through channel when setting interest rates. Finally, monetary surprises do not seem to be an important determinant of the evolution over time of the Taylor rule parameters, which suggests a high degree of monetary policy transparency in the countries under examination.

It provides new evidence on changes over time in monetary policy rules.

This paper seeks to explore the effect of performance duration (rather than intensity) on the subsequent initiation of strategic change by firms. Specifically, the effect of outperformance and underperformance duration on strategic change, as well as the moderating effect of environmental dynamism, is studied.

Using a fixed-effects model, analyzing a sample of 34,907 firm-year observations from 1980 to 2018 across 112 industries mostly supported proposed hypotheses.

Results revealed a U-shaped relationship between outperformance duration and strategic change and an inverted U-shaped relationship between underperformance duration and strategic change. The moderation role of environmental dynamism was only partially supported.

This study examines a new dimension of performance feedback, namely duration, rather than the widely used intensity of performance feedback, to enhance our understanding of the behavioral theory of the firm.

This study focuses on the work from home experiences of professional, middle and upper middle class married women with children in India during the COVID-19-induced lockdowns. This study aims to examine the experiences of changing nature of work and gendered realities of work–life balance for working mothers while working from home during the pandemic.

Semi-structured interviews were conducted with eight working mothers at three different time points during the lockdown in the city of Hyderabad in India.

A thematic analysis revealed changed work practices that required adapting, reinventing and reimagining new ways of working. This was time consuming albeit a satisfying experience for working mothers. At the same time, the blurring between home and work meant working mothers were operating without an off button.

The findings show that the existing gender inequalities in sharing the domestic burden unravelled fast in the absence of support structures.

The authors give voice to the lived experiences of working mothers of managing both work and home and how they navigated challenges during the lockdown.

This is the first article to apply a machine learning approach to the analysis of time on market on real estate markets.

The random survival forest approach is introduced to the real estate market. The most important predictors of time on market are revealed and it is analyzed how the survival probability of residential rental apartments responds to these major characteristics.

Results show that price, living area, construction year, year of listing and the distances to the next hairdresser, bakery and city center have the greatest impact on the marketing time of residential apartments. The time on market for an apartment in Munich is lowest at a price of 750 € per month, an area of 60 m2, built in 1985 and is in a range of 200–400 meters from the important amenities.

The findings might be interesting for private and institutional investors to derive real estate investment decisions and implications for portfolio management strategies and ultimately to minimize cash-flow failure.

Although machine learning algorithms have been applied frequently on the real estate market for the analysis of prices, its application for examining time on market is completely novel. This is the first paper to apply a machine learning approach to survival analysis on the real estate market.