Market Drivers Research Articles

Recessions and the stock market

An event study approach is adopted to investigate the drivers of the stock market around recessions. First, stock prices and dividends drop contemporaneously when accounting for different timing conventions. Accordingly, stock prices do not anticipate recessions due to an economic mechanism (cash flow news). Second, the variance of price changes increases at least as much as the variance of dividend growth during recessions. This result suggests that changes in the price of risk (discount rate news) play an essential role. Implications and opportunities for standard asset pricing theories and recently proposed alternatives are also discussed.

Relationship between the digital economy, resource allocation and corporate carbon emission intensity: new evidence from listed Chinese companies

Many studies have focused on the relationship between the digital economy and carbon emissions at the macro level. However, there is a relative dearth of research on this relationship at the micro level. In this study, we determined the impact of the digital economy on the carbon emissions of individual companies and the mediating role of resource allocation in this relationship using data from listed Chinese manufacturing companies between 2011 and 2019. This analysis yielded three main findings. First, based on firm-level carbon emissions and the borderless organization theory, we found that the digital economy significantly reduced corporate carbon emission intensity. Second, the digital economy reduced resource misallocation and improved resource efficiency, which in turn reduced corporate carbon emission intensity. Third, market drivers and government regulations improved and hindered the ability of the digital economy to reduce corporate carbon emission intensity, respectively. These findings provide evidence for the need for government investment in the development of digital technologies and corporate digitization; the use of digital technologies by businesses to improve resource and energy efficiency; and minimal government regulation of the digital economy in favor of self-regulation through market forces. These measures are important for economic transformation and the achievement of carbon neutrality in emerging developing countries, including China.

Beyond the ‘Field of Dreams’ model in smallholder forestry: Building viable timber value chains for smallholder tree growers in developing countries

Many smallholder tree growers in developing countries and those advising them, hold a view that if they plant trees a market will materialize when the time is right. However, despite strong international demand for timber and potential for smallholders to supply this demand, this ‘Field of Dreams’ approach, i.e. if you grow it, buyers will come, is not generally a sound strategy. In this study, we aimed to identify the conditions that enable the development of viable timber value chains around smallholder tree growers in developing countries. We reviewed literature on the integration of small-scale producers into value chains, smallholder tree growing, and smallholder commercial forestry to identify conditions, and used four case studies in the Asia-Pacific Region to understand how these influence outcomes for smallholder tree growers in different settings. This analysis provided a basis for recommendations for policymakers and advising agencies on how to support timber value chains for smallholder tree growers. These included deeper understanding of biophysical suitability of locations for tree growing, smallholder capabilities and interests, and provision of clear land tenure, infrastructure, and streamlined regulations sympathetic to smallscale timber operations. Tree growing can generate financial value for smallholders in regions with high human population density, quality road networks and proximity to processing markets and ports. Careful policy design is required to make it ‘fit for purpose’ at local levels, as conditions vary widely even within a single country. This can identify catalytic interventions and work with existing or near-term market drivers and simplified regulations in the value chain to generate benefits for smallholders.

5G AND 6G EVOLUTION

The constant evolution in telecommunications is recognized both as a market driver and as a driver for R&D, since R&D activities are built to support consumer and business demands. The market pressures and recent past recessions have considerably shifted the focus of companies to product development and incremental research. This current focus on short term gains has paved the way for applied research to the furthest extent. Research and technological development, which is a founding block of any field of science and technology, was explained from the point of view of ICT with a primary focus on the telecom industry. The research ecosystem along with its shortcomings were also presented. It is important that governments and the ICT industry re-evaluate the R&D ecosystem and consider having both a 3 to 5-year view along with a 30 to 40-year long vision. 5G technology started to roll out effectively to ordinary users in 2019 (development of this technology started in April 2008), and in 2020 it was expected to spread to even more countries, and then in a few years it will be global. This is despite various studies that point out that 5G radiation will have negative effects on human health (which has also been claimed for 4G and 3G), while organisations such as the US Communications Commission (US FCC) and almost all similar organisations state that 5G radiation has no significant effects on human health. Another concern is the security of communications over 5G networks, especially equipment sold by China. Australia and the UK – in early 2019, took steps to restrict or eliminate the use of Chinese-sourced equipment in their 5G networks. Also in 2019 the US via the FBI and the UK via Government Communications Headquarters (GCHQ) other intelligence services, began to get more involved in changing surveillance standards. Including at the NATO meeting in London in December 2019, 5G network security and development was discussed. In addition to high download speeds, the 5G network also has a low “air latency” (between phone and antenna) of 8-12 milliseconds.

Intelligent logistics transformation problems in efficient commodity distribution

In recent years, comprehensive information, intelligence and automation technology have become the emerging development trend in distribution enterprises. Intelligent logistics transformation (ILT) is the basis of realising efficient commodity distribution. However, the real-time practice of implementation of ILT is not running smoothly in China. This is caused by a lack of a theoretical framework of causes of intelligent logistics transformation problems (ILTP) in efficient commodity distribution that helps enterprises avoid problems. This pilot study proposes a conceptual model of ILTP based on the grounded theory and tests it by a survey in application to efficient commodity distribution. There are five major factors influencing ILTP in efficient commodity distribution: inherent risks of transformation, difficulties in organizational adjustment, market obstacles, market drivers and social factors. The inherent risks of transformation and difficulties in organizational adjustment are direct factors affecting the ILTP, while market obstacles, market drivers and social factors moderate significantly these relations. The key contribution of this paper provides firms and governments with relevant management and policy recommendations to implement the ILT in the context of the efficient commodity distribution.

Does money laundering inflate residential house prices? Evidence from the Italian provincial markets

AbstractIn this paper, we provide an estimate of the impact of money laundering on residential house market prices. The housing market is commonly exploited by criminal organizations to clean illegal profits. The increase in demand due to money laundering contrasts the negative externality of crime on house prices, which has been investigated by a large literature. We build a new dataset on residential house prices at the provincial level in Italy over the period 2005–2012, obtaining a sample of 672 observations. We then estimate a hedonic equilibrium price model, controlling for proxies both for illegal profits derived from “entrepreneurial” crimes (drug dealing, receiving stolen goods, prostitution) and for violent crimes (extortions), together with traditional market drivers. Adding to the evidence from the traditional literature, which remarks the negative impact of crime on house prices, our findings suggest that money laundering from “entrepreneurial” crimes creates an upward distortion in the housing market prices. The impact is stronger where retail markets for illicit trades are richer.

Competition and coopetition for two‐sided platforms

Two‐sided platforms have become omnipresent. In this context, firms compete not only for customers but also for flexible self‐scheduling workers who can work for multiple platforms. We consider a setting where two‐sided platforms simultaneously choose prices and wages to compete on both sides of the market. We assume that customers and workers each follow an endogenous generalized attraction model that accounts for network effects. In our model, the behavior of an agent depends not only on the price or wage set by the platforms, but also on the strategic interactions among agents on both sides of the market. We show that a unique equilibrium exists and that it can be computed using a tatônnement scheme. The proof technique for the competition between two‐sided platforms is not a simple extension of the traditional (one‐sided) setting and involves different arguments. Armed with this result, we study the impact of coopetition between two‐sided platforms, that is, the business strategy of cooperating with competitors. Motivated by recent practices in the ride‐sharing industry, we analyze a setting where two competing platforms engage in a profit sharing contract by introducing a new joint service. We show that a well‐designed profit sharing contract (e.g., under Nash bargaining) will benefit every party in the market (platforms, riders, and drivers), especially when the platforms are facing intensive competition on the demand side. However, if the platforms are facing intensive competition on the supply side, the coopetition partnership may hurt the profit of at least one platform.

Market-shaping roles – Exploring actor roles in the shaping of the Swedish market for liquefied gas

Despite the emphasis on actors in the market-shaping literature, the market-shaping roles and heterogeneity of market actors have mostly been aggregated into overarching practices, processes, or activities. While market-shaping research has provided rich insights into the different activities, and actors, that play a role in shaping markets, it remains unclear how the differences in market actors' market-shaping engagement translate back into specific roles. By following the Swedish market for liquefied gas over a period of three years, this longitudinal case study draws on extensive data to further elucidate market-shaping processes through the lens of roles. Employing an abductive theorizing approach, we empirically investigate the different roles performed by market actors in market-shaping processes. We discover that roles depend on the different levels in market-shaping engagement towards a focal market vision that ultimately relates to the disposition, behavior and influence displayed by the specific actors. Within this process we identify and delineate six market-shaping roles: the Market Driver, Market Supporter, Market Missionary, Market Rival, Market Catalyzer, and Market Detractor.

Harnessing AI for business development: a review of drivers and challenges in Africa

An accumulating body of research has demonstrated that artificial intelligence (AI) is an indistinguishable feature of the fourth industrial revolution. This study integrates the literature on AI and new technologies to examine the constraining and facilitating forces for developing and scaling-up AI-enabling technologies in Africa. This article proposes an integrated conceptual model to elucidate the range of external drivers encompassing global competitive drivers, and market and industry drivers. The internal drivers include the potential to enhance product development speed, improve quality, drive production cost down, and minimise errors and manual processes in organisations. The barriers identified include institutional dysfunction, poor infrastructure to support development of large-scale AI, lack of skilled AI experts, and lack of access to latest technologies in the regional population. The public policy implications for Africa as the potential next frontier market for AI development are discussed alongside contributions to theory.

Smallholder Coffee in the Global Economy—A Framework to Explore Transformation Alternatives of Traditional Agroforestry for Greater Economic, Ecological, and Livelihood Viability

Sixty percent of global coffee is produced from farms of <5 ha. Studies show that returns from such farms do not generate a living income for producers or workers threatening supplies. Smallholders use agroforestry to reduce coffee production costs, diversify income and address livelihood needs. We undertook a three-phase analysis to test the following hypothesis. Current coffee agroforestry must shift from a low labor, low risk-stable return, slowly-changing matrix to more active management of species and stem turnover in system renovation cycles targeted to sustaining, reorienting and intensifying ecosystem-based benefits to coffee production, diversified income and household food. First, we conducted a document survey of current traditional tree diversity, research trends, and market drivers for more benefits-oriented agroforestry. Second, we proposed a framework for multiple benefits quantification converting tree use characteristics and density into five categories of benefits, each with sub-categories which we tested using previously collected data of stem density by species from coffee agroforestry in northern Nicaragua. Third, we modeled radiation in mixed canopy scenarios using the program SExI- FS based on modifications of species and density to target food and income diversification and tested our framework by quantifying benefits. We found that smallholder coffee faces farms decreasing coffee margins, labor scarcity, new pests and climate variability best addressed with targeted and adaptive shifts in coffee varieties and associated trees. Increasing data demands from certification and regulations provide a basis more data-driven coffee farm management. Our data bases of stem density by species of established agroforestry systems were sufficient to identify gaps in food and income benefits which were addressed in the scenarios thereby verifying the hypothesis. The benefits ranking both of current systems and three scenarios also provided insights into data collection specifications for a more rigorous academic test of the hypothesis and data-driven grower strategies for agroforestry transformation.

A Review On The Synthesis Strategies For The Fabrication Of Superhydrophobic Coating

Over the past few years, superhydrophobic coating exhibiting unique structure and exceptional water repellency has emerged as a versatile coating for the applications in the field of anti-corrosion[1], anti-icing 2], anti-fogging[3], self-cleaning[4], anti-fouling[5], and medical sectors. Recent progress in the underwater and flexible electronics, automotive, advanced textiles, high end footwear, and food packaging industry sectors are expected to act as crucial growth drivers of this superhydrophobic market in the future. Self-cleaning and water-repellent behaviors are governed by the ‘wettability’ of a material surfaces as naturally found in lotus leaf, peanut leaf, rose petals, poplar leaf, Salvinia molesta floating leaves, butterfly wing, fish scale, water strider, compound eyes of mosquito, gecko feet, desert beetles, spider silk, cactus, and many more. In general, to what extent a material is wet with a liquid is determined by the balance of surface free energy and roughness. With the advent of nanotechnology and nanomaterials, surface architecture as well as surface chemistry can be controlled to obtain superhydrophobicity. Surface chemistry alone may not be adequate to explain the superhydrophobic behavior. It appears to be a physiochemical phenomenon, where substrate is a function of two key aspects comprising surface chemistry and surface architecture. This can be achieved by incorporating lower surface energy species to the surface.

Do Agricultural Advisory Services in Europe Have the Capacity to Support the Transition to Healthy Soils?

The need to provide appropriate information, technical advice and facilitation to support farmers in transitioning towards healthy soils is increasingly clear, and the role of the Agricultural Advisory Services (AAS) in this is critical. However, the transformation of AAS (plurality, commercialisation, fragmentation, decentralisation) brings new challenges for delivering advice to support soil health management. This paper asks: To what extent do agricultural advisory services have the capacity to support the transition to healthy soils across Europe? Using the ‘best fit’ framework, analytical characteristics of the AAS relevant to the research question (governance structures, management, organisational and individual capacities) were identified. Analysis of 18 semi-structured expert interviews across 6 case study countries in Europe, selected to represent a range of contexts, was undertaken. Capacities to provide soil health management (SHM) advice are constrained by funding arrangements, limited adviser training and professional development, adviser motivations and professional cultures, all determined by institutional conditions. This has resulted in a narrowing down of access and content of soil advice and a reduced capacity to support the transition in farming to healthy soils. The extent to which emerging policy and market drivers incentivise enhanced capacities in AAS is an important area for future research.

The European Union as a destination of Turkish migrants in 2008–2018

AbstractIn the 1950s and 1960s, Europe was a popular migration destination for Turkish people due to its employment opportunities. Today, however, these labor market drivers of migration destinations in the EU-28 have been superseded. This article empirically investigates the drivers of the migration destinations of Turkish newcomers to EU countries between 2008–2018. It contributes to the literature by focusing only on Turkish newcomers, whereas other studies rely on migration stock data. Using data provided by the OECD, Eurostat, and the World Bank, the findings show that security-based and social drivers mostly attract Turkish newcomers to EU-28 destinations, specifically a demand for democracy and social networks.

Unravelling the Drivers of Plantain Marketing in Enugu State, Nigeria

Plantain marketing offers great profit-making, yet it is unclear if this has translated to more profits, making it imperative to examine the drivers of plantain marketing. Primary data collected with a structured questionnaire in the purposive 2-staged random sampling were analyzed using net marketing income, marketing margin, marketing efficiency and multiple linear regression models. Plantain marketing was mainly done by married educated women, averaging 40 years of age, belonging to households averaging 6 persons. Net monthly profit of $63.51 (₦26,050.38), average marketing margin of 30.84% and marketing efficiency of 35.06% were returned. Suggesting plantain marketing is profitable and viable but largely inefficient. The cost of plantain and marketing experience were positively significant (p≤0.05). Plantain marketing faced constraints like the seasonality of plantain, inadequate finance, price fluctuations, high transportation costs, bulkiness, spoilage/breakage and high plantain costs. Plantain marketers should form/join cooperatives to obtain low-interest loans, mitigate marketing costs and enjoy economies of scale.

Public policies versus market factors: What drives ethanol expansion in Brazil?

Abstract Concerns about energy security, rural development, and the environment have driven biofuel expansion. Different policy and market drivers, such as designated areas for biofuel feedstock production and blend mandates, have played an important role in biofuel expansion in different countries. Understanding how policy and market drivers influence biofuel supply and demand can provide guidelines for countries seeking to expand biofuel production into new regions. The case of Brazil serves as an important example. In just over 10 years, the Cerrado region of Brazil, specifically the states of Goias and Mato Grosso do Sul, experienced a six-fold expansion in ethanol production, becoming the second largest production region in Brazil. The purpose of this study is to examine the influence of policies and market drivers on ethanol expansion in the Cerrado region using a market equilibrium modeling approach. Results elucidate the role that market and policy drivers, including areas designated for sugarcane production, blend mandates, and energy taxes, play in influencing ethanol expansion into an already intensive agricultural region of the country. The findings from this study have implications for sustainable biofuel production in other regions of the world.

Defend as You Can, React Quickly: The Effects of the COVID-19 Shock on a Large Fishery of the Mediterranean Sea

This paper presents an analysis of the effect of SARS-CoV-2 coronavirus pandemic and related restrictive measures on the activity of the Italian fleet of trawlers, which represents one of the most important fisheries in the Mediterranean Sea. We integrated multiple sources of information including: (1) Fleet activity data from Vessel Monitoring System, the most important satellite-based tracking device; (2) vessel-specific landing data disaggregated by species; (3) market and economic drivers affecting the effort variation during the lockdown and in the related fishing strategies; (4) monthly landings of demersal species in the main Italian harbors. These data sources are combined to: (1) Assess the absolute and relative changes of trawling effort in the geographical sub-areas surrounding the Italian coasts; (2) integrate and compare these changes with the market and economic drivers in order to explain the observed changes in fishing effort and strategy; (3) analyze the changes of the fishing effort on the Landing-per-unit-effort (LPUE) in order to further understand the strategy adopted by fishers during this crisis and to infer the potential consequence for the different stocks. The results provide an overview of the effects of the “COVID-19 shock,” in terms of fishing activity and socio-economic drivers, demonstrating that the consequences of the pandemic have been very varied. Although the COVID-19 shock has caused a marked overall reduction in activity in the first semester of 2020, in some cases the strategies adopted by fishermen and the commercial network linked to their activity have significantly reduced the impact of the emergency and taken back catch and effort to levels similar to those of previous years. These results could provide insights for management measures based on temporal stops of fishing activities. In particular, if no limits to the fishing effort after the restart of fishing activities are adopted, the benefits of fishing pressure reduction on fishery resources could be nullified. On the other hands, when fishing activities restart, and in the absence of catch control, effort tends to increase on coastal bottoms characterized by greater abundance of resources and longer effective fishing time.

The role of market drivers in explaining the EU milk supply after the milk quota abolition

The abolition of the EU milk quota system since 2015 has allowed the dairy sector to fully react to market forces. This change should be properly reflected within the tools that support the design of EU/national policy interventions. This paper focuses on updating the milk supply responses at EU member state level in a context where still limited data is available. Using a Mixed Estimator a set of equations for the yield per cow and the size of the dairy herd, has been estimated, leaving the milk supply derived as an identity. An important outcome of this study is that milk supply at country level is inelastic, with the (short-run) yield and herd milk price elasticities being 0.2 and 0.1 respectively. The study concludes that two thirds of the impact of a milk price change is resulting from dairy cow yield changes, while a third is resulting from changes in the number of dairy cows.

Market complete option valuation using a Jarrow-Rudd pricing tree with skewness and kurtosis

Applying the Cherny-Shiryaev-Yor invariance principle, we introduce a generalized Jarrow-Rudd (GJR) option pricing model with uncertainty driven by a skew random walk. The GJR pricing tree exhibits skewness and kurtosis in both the natural and risk-neutral world. We construct implied surfaces for the parameters determining the GJR tree. Motivated by Merton’s pricing tree incorporating transaction costs, we extend the GJR pricing model to include a hedging cost. We demonstrate ways to fit the GJR pricing model to a market driver that influences the price dynamics of the underlying asset. We supplement our findings with numerical examples.

From fault-detection to automated fault correction: A field study

A fault detection and diagnostics (FDD) tool, as addressed by this study, is a tool that continuously identifies the presence of faults and efficiency improvement opportunities through a one-way interface to the building automation system and the application of automated analytics. Although FDD tools can inform operators of building operational faults, currently an action is always required to correct the faults to generate energy savings. Fault auto-correction integrating with commercial FDD technology offerings can close the loop between the passive diagnostics and active control, increase the savings generated by FDD tools, and reduce the reliance on human intervention. This paper presents the field study of seven fault auto-correction algorithms implemented in commercial FDD platforms. Implementation includes software changes in the FDD tools and additional controls hardware or software changes in the BAS that were required to enable the execution of different types of auto-correction algorithms in real buildings. The routines successfully and automatically correct faults and improve the operation of large built-up Heating, Ventilation, and Air Conditioning (HVAC) systems, common in most commercial buildings. The auto-correction algorithms are tested across four buildings and three different building automation systems, following a rigorous procedure to make sure they work properly and do not negatively impact the system and building occupants. Technology benefits, market drivers, and scalability changes are drawn from the implementation effort and test results, to drive future research and industry engagement.

Discovering the fundamentals of Turkish housing market: a price convergence framework

PurposeThe purpose of this study is to determine the Turkish housing price and rent dynamics among seven big cities with a unique monthly data set over 2003–2019. The secondary purpose is to examine bubble dynamics within the price convergence framework through alternative tests.Design/methodology/approachThe paper conducts two autoregressive distributed lag (ARDL) cointegration estimates for housing prices and rents and applies conditional error correction model to investigate the long-run drivers of the Turkish housing market. The authors compare ARDL cointegration in-sample forecasts and discounted cash flow (DCF) estimates with actual prices to determine the timing, magnitude and collapse period(s) of bubbles within the price convergence framework. In particular, the generalized sup augmented Dickey–Fuller (GSADF) approach time stamps multiple explosive price behaviors.FindingsThe ARDL results confirm the theory of investment value by addressing mortgage rates, the price-to-rent ratio and rents as the fundamental factors of house prices. The price-to-rent ratio offers a comparison mechanism among houses deciding to buy a new house in which rents increase monthly real estate investment returns, and mortgage rates act as the discount rate. One key finding is that these dynamics have a greater impact on house prices than mortgage rates. Furthermore, the ARDL, DCF and GSADF findings exhibit temporal overvaluations rather than bubble signals, implying that housing price appreciations, including explosive behaviors, are consistent with fundamental advances.Originality/valueThis paper is considered to be innovative in determining housing market dynamics through two different ARDL estimates for the Turkish housing price index and rents in real terms as dependent variables. The authors compare the boom and collapse periods of the real housing price index and its fundamentals via the GSADF test. A final key feature of this research is its extensive data set, with 11 different regressors between 2003 and 2019.