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We examine the impact of oil price uncertainty on IPO volume in the oil and gas sector. By using the implied volatility of oil options, a forward looking exogenously determined uncertainty measure, we can clearly identify the effect of uncertainty on the going public decision. Oil price uncertainty has a strong negative relation to IPO volume, a one standard deviation decrease in the implied volatility results in a 25%-29% increase in the number of quarterly IPOs. The effect is concentrated among the price sensitive upstream producers. We further report that uncertainty negatively impacts the IPO withdrawal decision and increases the value to postpone the offering.

Many electricity markets in the world have experienced the vertical unbundling where the generation and transmission sectors were separated from a vertically-integrated monopolistic power company. This restructuring could positively impact the productivity of the firms because of intensified competition and enhanced autonomy but could also negatively affect the productivity because of the loss of synergy and scaled economy. By exploiting the vertical unbundling that took place in China in 2003, this study finds that vertical unbundling increased the labor use of the generation firms and the material use of the transmission firms. Additional investigation reveals that generation firms suffer from an efficiency loss in labor use due to the loss of coordination after vertical unbundling and the transmission firms face an increased transaction cost in acquiring material and bear the additional cost transferred from the efficiency loss of the upstream generation firms. Our findings suggest that benefits of vertical unbundling relative to integration critically hinge on the market structure of the industry.

When multiple retailers hold inventory to satisfy random demand, retailer inventory-sharing strategies can potentially reduce the supply-demand mismatch and increase overall supply chain performance. In this paper, we experimentally investigate alternative inventory-sharing strategies in a two-tier supply chain with an upstream manufacturer and two downstream retailers. In one setting, retailers act as if they are centralized and use a single quantity to fulfill joint demand. In the other, retailers are decentralized and face separate demands, but they can transfer inventory after demands are realized. In this latter decentralized scenario, we also consider whether the manufacturer or retailers have decision authority over the inventory transfer price. One key result is that when the retailers are decentralized and the manufacturer sets the transfer price, both retailers and the manufacturer earn higher profits than in the centralized retailer strategy, which runs counter to theory. We also find that when retailers are decentralized and set their own transfer price, the most equitable distribution of profits is achieved. In an effort to account for these results, we find that a model of fairness captures decisions well. Overall, by investigating how different inventory-sharing strategies affect the distribution of profits in a two-tier supply chain, our results provide guidance to firms considering how, if at all, they should enter such arrangements. This paper was accepted by Jay Swaminathan, operations management. Funding: The authors acknowledge financial support from Cornell University and the University of Virginia. Supplemental Material: The data files and electronic companion are available at https://doi.org/10.1287/mnsc.2022.4323 .

While economic theories indicate that market power by downstream firms can potentially counteract market power upstream, antitrust policy is opaque as to whether to incorporate countervailing market power in merger analyses. We use detailed national claims data from the health care sector to evaluate whether countervailing insurer power does indeed limit hospitals' exercise of market power. We estimate willingness-to-pay models to evaluate hospital market power across analysis areas. We find that countervailing market power is important: a typical hospital merger would raise hospital prices 4.3% at the 25th percentile of insurer concentration but only 0.97% at the 75th percentile of insurer concentration.

The modern day food industries are part of a complex agri-food supply chain, where food production has become efficient, yet potentially vulnerable to supply chain risks. The COVID-19 pandemic is a testament to that end. This article measures and identifies the U.S. food manufacturing industries' vulnerability to upstream industries and labor occupations by (i) calculating a food industry's diversification of intermediate input purchases across upstream industries, (ii) quantifying the relative exposure of food manufacturing in a given industry and location to upstream input suppliers and labor occupations, and (iii) estimating each food industry's gross output elasticity of inputs. Among our results, we find the evidence that the animal processing industry's output is relatively vulnerable to production labor which is consistent with the observed disruptions to the meat packing sector during COVID19, which were largely caused by labor issues. Our results may help academics and practitioners to understand food industries' vulnerabilities to upstream industries and labor occupations.

This paper examines the morning commute problem when both household commuters and individual commuters are considered in a Y-shaped network with two upstream links and a single downstream link. The household parents daily pass through an upstream bottleneck with a limited capacity before a school and drop off their children. Then, they traverse the downstream bottleneck common to both household and individual commuters and arrive at the workplace. We explore the effects of staggering policy, that is, staggering work and school start times, on the distribution of traffic congestion and social welfare. We analytically solve all the equilibrium cases and reveal all the traffic congestion patterns. The results reveal that the staggering policy may be harmful in certain cases. When the demand of individuals is relatively low, the staggering policy may not improve social welfare. When the demand of individuals is high, social welfare can be significantly improved if the schedule gap between the work start time and school start time is optimized. The effects of the staggering policy on system performance are examined. We derive a Pareto frontier, which provides a good candidate set for policymakers when the two system performance measures, that is, the total system cost and the total congestion cost, are considered. Our results show that the optimal staggering policy on system performance depends on the demand distribution of the two groups. When the demand of individuals is high, there exists a unique optimal staggering policy that optimizes system performance. However, when the demand of individuals is low, the optimal staggering policy should be selected from the Pareto frontier. Furthermore, we re-examine the capacity expansion paradox under the staggering policy. Our study shows the capacity expansion at the downstream bottleneck can always reduce the total system cost. However, the paradoxical phenomenon may arise when the capacity of the upstream bottleneck is expanded, but it can be eliminated if the schedule gap is properly designed. Ministry of Education (MOE) Nanyang Technological University This research was funded by National University of Singapore, Singapore Ministry of Education Academic Research FundTier 2 [Grant MOE2017-T2-2-128]; Dalian University of Technology, National Natural Science Foun-dation of China [Grant 71533001]; Nanyang Technological University, Singapore Ministry of Educa-tion Academic Research Fund [Grant MOE2017-T2-2-093]; Dalian University of Technology, ChinaScholarship Council.

This paper examines the impact of Covid‐19 lockdowns on exports by Chinese cities. We use city‐level export data at a monthly frequency from January 2018 through April 2020. Differences‐in‐differences estimates suggest cities in lockdown experienced a ceteris paribus 34 percentage points reduction in the year‐on‐year growth rate of exports. The lockdown impacted the intensive and extensive margin, with higher exit and lower new entry into foreign markets. The drop in exports was smaller in (i) coastal cities; (ii) cities with better‐developed ICT infrastructure; and (iii) cities with a larger share of potential teleworkers. Time‐sensitive and differentiated goods experienced a more pronounced decline in export growth. Global supply chain characteristics matter, with more upstream products and industries that had accumulated larger inventories experiencing a smaller decline in export growth. Also, products that relied more on imported (domestic) intermediates experienced a sharper (flatter) slowdown in export growth. The rapid recovery in cities' exports after lockdowns were lifted suggests the policy was cost‐effective in terms of its effects on trade.

As economic development upstream in the Yangtze River basin has progressed in recent decades, the demand for sediment has rapidly increased and contributed to an expansion in sediment excavation that may affect the river's stability and navigation safety. In the current study, the distribution of gravel mining in the upstream reach of the Yangtze River was investigated using field measurements obtained from 2008 to 2017. An experimental investigation was then done to analyze the bed load behavior in a typical mined channel using a physical river model. Finally, a two-dimensional hydrodynamic-sediment transport numerical model was developed to predict the evolution of the mined channel. The results indicate that gravel mining was mainly distributed among the following nine river sections: Tongluoxia–Yibin, Erlong–Xianglutan, Naxi–Jinkou, Binpangqi–Hongyanqi, Chayuqi–Shenbeizui, Yangshipan–Shangbaisha, Dongxikou, Baisha–Wenzhongba, and Jiangjin– Shenzhongba. The gravel shoals near the riverbank have been destroyed, and the bed topography has been altered by up to 1.65 × 109 m3 over the past 10 years. A bed load velocity formula was proposed to describe bed load transport in the mined channel based on dimensional analysis. The recovery process of the excavation pits was slow in both the experiments and simulations, with only 0.12 and 1.39%, respectively, of the mined amounts of gravel being restored. Finally, the recovery rate of the mining pits gradually slowed as the sediment supply from upstream decreased, suggesting that the destroyed gravel shoals rarely returned to their original forms due to the combined operation of hydro-projects in upstream areas and limited sediment storage in the channel.

In the Oil and Gas industry, the implementation of artificial intelligence techniques gives advantages of better use of existing infrastructure. It provides better future outcomes, which makes it an essential technology in the operations of the industry. In this paper, the implementation of artificial intelligence techniques for good planning, determination of reservoir rock properties, drilling optimization and production facilities are reviewed. With precise knowledge of permeability and porosity, reservoir engineers can develop robust reservoir development plan and manage hydrocarbon recovery effectively. For porosity prediction, wire-line log data and seismic attributes are used in artificial intelligence-based models. Permeability prediction has been discussed by considering the different types of well-log data in the modeling of artificial intelligence techniques to predict single-phase fluid. Solution of specific developed problems during the determination of permeability in the actual experiment is also mentioned. Artificial intelligence techniques are used in the design and accurate analysis of the drilling fluid. It assists in the selection of drill bit and drilling-related problems. If a reservoir cannot produce naturally, we can select a suitable artificial lift and design the production system using Artificial intelligence techniques. For EOR methods, SADA and NAVA knowledge base systems are discussed. Artificial intelligence can help in optimizing production, improve production efficiency and recovery of hydrocarbons.

Reconstruction of natural streamflow is fundamental to the sustainable management of water resources. In China, previous reconstructions from sparse and poor-quality gauge measurements have led to large biases in simulation of the interannual and seasonal variability of natural flows. Here we use a well-trained and tested land surface model coupled to a routing model with flow direction correction to reconstruct the first high-quality gauge-based natural streamflow dataset for China, covering all its 330 catchments during the period from 1961 to 2018. A stronger positive linear relationship holds between upstream routing cells and drainage areas, after flow direction correction to 330 catchments. We also introduce a parameter-uncertainty analysis framework including sensitivity analysis, optimization, and regionalization, which further minimizes biases between modeled and inferred natural streamflow from natural or near-natural gauges. The resulting behavior of the natural hydrological system is represented properly by the model which achieves high skill metric values of the monthly streamflow, with about 83% of the 330 catchments having Nash-Sutcliffe efficiency coefficient (NSE) > 0.7, and about 56% of the 330 catchments having Kling-Gupta efficiency coefficient (KGE) > 0.7. The proposed construction scheme has important implications for similar simulation studies in other regions, and the developed low bias long-term national datasets by statistical postprocessing should be useful in supporting river management activities in China.

The Mediterranean diet is appraised as the premier dietary regimen, and its espousal is correlated with the prevention of degenerative diseases and extended longevity. The consumption of olive oil stands out as the most peculiar feature of the Mediterranean diet. Olive oil rich in various bioactive compounds like oleanolic acid, oleuropein, oleocanthal, and hydroxytyrosol is known for its antiinflammatory as well as cardioprotective property. Recently in silico studies have indicated that phytochemicals present in olive oil are a potential candidate to act against SARS-CoV-2. Although there are many extensive studies on olive oil and its phytochemical composition, however, some lacunas persist in understanding how the phytochemical composition of olive oil is dependent on upstream processing. The signaling pathways regulated by olive oil in the restriction of various diseases are also not clear. For answering these queries, a detailed search of research and review articles published between 1990 to 2019 were reviewed. Olive oil consumption was found to be advantageous for various chronic non-communicable diseases. Olive oil’s constituents are having potent anti-inflammatory activities and thus restrict the progression of various inflammation-linked diseases ranging from arthritis to cancer. But it is also notable that the amount and nature of the phytochemical composition of household olive oil are regulated by its upstream processing, and the physicochemical properties of this oil can give a hint regarding the manufacturing method as well as its therapeutic effect. Moreover, daily uptake of olive oil should be monitored as excessive intake can cause body weight gain and a change in the basal metabolic index. So, it can be concluded that the olive oil consumption is beneficial for human health, and particularly for the prevention of cardiovascular diseases, breast cancer, and inflammation. The simple way of processing olive oil is to maintain the polyphenol constituents, whichprovide the protection against noncommunicable diseases and SARS-CoV-2.

Coopetition is a business phenomenon that dominates many supply chains. We aim to understand why and how coopetition occurs in supply chains with the presence of process improvement in upstream component production. An original equipment manufacturer (OEM) can purchase the component from either a non-competing supplier (NS) or a competing supplier (CS) that also sells substitutable products in the end consumer market. We demonstrate that without process improvement, coopetition does not exist, because the OEM prefers sourcing from the NS, even though the CS is willing to sell the component to the OEM. Two cases are considered in which process improvement is present: supplier-initiated investment, where the suppliers conduct self-investment, and OEM-initiated investment, where the OEM invests in the supplier's process. We find that with supplier-initiated investment, the CS always prefers coopetition, but the OEM may not. When the investment is efficient, coopetition occurs as an equilibrium outcome; otherwise, competition occurs. The cause of coopetition equilibrium comes from variable process improvement incentives of the CS that derive from two driving forces: the vertical wholesale price effect and the horizontal quantity competition effect. When the degree of product substitution is low, the CS increases its investment and lowers its wholesale price, benefiting the OEM. When the degree of product substitution is high, the CS reduces its investment as well as production quantity, which also benefits the OEM. Interestingly, with OEM-initiated investment, the CS might not always choose to sell the component to the OEM, and as a result, coopetition never occurs.

We construct a sample of over 200,000 supply chains between 2003 and 2018 to conduct a chain-based analysis of trade credit. Our study uncovers novel stylized facts about trade credit both within and across supply chains. More upstream firms borrow more from suppliers, lend more to customers, and hold more net trade credit. This upstreamness effect in trade credit is weaker for more profitable firms and for longer chains. Firms in more central or more profitable chains provide more net trade credit. Our results are generally consistent with the recursive moral hazard theory of trade credit. Evidence for the financing advantage theory is mixed.

Ancillary service providers (ASPs) on an inpatient unit (IU), such as social workers, care managers, and physical and occupational therapists, play crucial roles in the inpatient discharge process. However, on a typical day, these ASPs must balance the needs of newly arriving, recurring, and outgoing patients (discharges). While prioritizing the discharges is shown to improve the hospital patient flow and bed utilization, the needs of the other patients cannot be neglected. We examine whether patient sequencing strategies for these ASPs can be found that maintain patient care and optimize patient flow. We approach this ASP workload sequencing problem by proposing a stochastic optimization model and developing a simulated annealing algorithm to derive sequencing strategies that are easy to implement and promising to all scenarios. Our experimental results suggest that patients with pressing constraints should be prioritized over discharges, with discharges then prioritized over other patients. As the complexity of the workload increases (a large number of patients and/or a high percentage of discharges), the focus should shift more towards discharges. We further evaluate the performance of our derived strategies against simpler realistic ASP sequencing strategies and classical machine scheduling rules. Our strategies consistently perform well on deviation from the optimal upstream boarding time and always ensure that patient constraints are met; other simpler strategies can outperform ours only at the cost of increases in cutoff and due-date violations. This paper reveals the importance of a systemic view (inpatient and upstream) on the part of the ASP when prioritizing patients in an IU.

Raw fresh-milk has a perishable characteristic, so it needs an appropriate handling from milking to processing, otherwise fresh milk will be contaminated by bacteria so that the shelf life becomes shorter and its losses the quality. Besides, from the perspective of quantity, the lower farmer’s production in the upstream will minimizes the product availability in the downstream. This condition may cause some potential risk during the supply chain. There is a need to map the risk along the supply chain, using samples in Tirunelveli Aavin Nellai milk plant. This paper aimed to analyze the pattern of the supply chain and its risk, to set the risk treatment and to mitigate the risk as well. Data sampling were selected by simple random sampling and then collected using in-depth interview to the risk owners. The results show there are 6 supply chain models and the total number of risks is 50 some of the risks are repeated and from that 10 prioritized risks are mitigated.

The process of river avulsion builds floodplains and fills alluvial basins. We report on a new style of river avulsion identified in the Landsat satellite record. We found 69 examples of retrogradational avulsions on rivers of densely forested fluvial fans in the Andean and New Guinean alluvial basins. Retrogradational avulsions are initiated by a channel blockage, e.g., a logjam, that fills the channel with sediment and forces water overbank (dechannelization), which creates a chevron-shaped flooding pattern. Dechannelization waves travel upstream at a median rate of 387 m/yr and last on average for 13 yr; many rivers show multiple dechannelizing events on the same reach. Dechannelization ends and the avulsion is complete when the river finds a new flow path. We simulate upstream-migrating dechannelization with a one-dimensional morphodynamic model for open channel flow. Observations are consistent with model results and show that channel blockages can cause dechannelization on steep (10−2 to 10−3), low-discharge (~101 m3 s−1) rivers. This illustrates a new style of floodplain sedimentation that is unaccounted for in ecologic and stratigraphic models.

Oil and gas activities are a major source of methane and in recent years multiple companies have made pledges to cut their emissions of this potent greenhouse gas. Satellites are a promising technology, but their relevance to emissions reconciliation and reporting has not yet been independently established. In this review paper, we assess the capabilities of satellites to determine their role in emissions detection, reconciling and reporting in the upstream section of the oil and gas value chain. In reconciling, satellites have a role in verifying emissions estimated by other technologies, as well as in determining what is causing discrepancies in emission estimates. There are many limitations to satellite usage which need to be addressed before their widescale or routine use by the sector, particularly relating to where they can be used, and high uncertainty associated with their emission estimates. However, where limitations are overcome, satellites could potentially transform the way emissions are reconciled and reported through long-term monitoring, building emission profiles, and tracking whether emission targets are being met. Satellites are valuable tools, not just to the oil and gas sector but to international governments and organisations, as abating methane is crucial for achieving Paris Agreement ambitions.

The company builds communication and collaboration with suppliers and customers to increase competitiveness in the supply chain flow. The organization's ability to involve suppliers and customers in business activities to achieve efficiency and effectiveness is one of the objectives of supply chain practice. The distribution of questionnaires directly to hotel practitioners was 25 respondents, and 65 respondents obtained the distribution of google form links. The results showed that supply chain practices with supplier relationship management and quality information sharing activities could increase internal and upstream integration and not directly impact downstream integration. Internal integration with data integration activities accurately and coordination between functions on an ongoing basis can affect upstream and downstream integration and green hotel performance. Upstream integration and downstream integration with joint decision activities and planning synchronization with external parties can directly impact green hotel performance. They were increasing the market share and image of the hotel with the implementation of caring for the environment. This research contributes to hotel practitioners adopting practical supply chains in building internal and external integration to increase competitiveness and theoretical contribution to developing supply chain theory and green performance.

A three-year research project explored the evolving level of “building expertise” for low-carbon housing refurbishment in the UK and France. With a focus on “middle actors” and the evolution of professional practice, this paper reports on “middle-out” responses from the housing retrofit supply chain to top-down policies promoting low-energy retrofits of existing homes. The two countries have comparable long-term policy goals for CO2 emissions reduction, but there are important differences between their more immediate initiatives to achieve a step-change in activity in the housing retrofit market. Industry responses to these various policy signals were explored in a series of semi-structured interviews with builders involved in innovative, low-energy refurbishment projects. Drawing mainly on four case studies of innovative business models, the paper highlights innovative practices and processes being proposed and trialled by “middle actors” in the building industry. We describe middle-out implications of these innovative practices: upstream to policy makers, downstream to clients, and sideways across refurbishment providers and the retrofit supply chain.

Purpose The purpose of this study is to theoretically and empirically advance a concept of competitive antecedents to absorptive capacity (AC) research and to explain their relationship to a firm’s innovative performance. A firm’s competitive antecedents involve a relative advantage in a firm’s ability to access external knowledge – (i.e. relative advantage in external knowledge flows) – and a relative advantage in appropriating these external knowledge flows (i.e. relative advantage in appropriability regime). Design/methodology/approach By drawing on network and market share explanations, hypotheses were developed in which a firm’s AC is argued to mediate the influence of these competitive antecedents on a firm’s innovations. In using linear and negative binomial estimation methods, a mediation analysis of the US biotechnology industry was conducted. Findings A firm’s competitive antecedents have a positive influence on a firm’s AC and that these influences indirectly impact a biotechnology firm’s product innovations. Originality/value While a firm’s innovation is widely attributed to its AC, this study’s concept of competitive antecedents shows that a firm’s competitive advantage lies upstream from its AC.

This study extends the understanding of entrepreneurial orientation (EO), vertical knowledge acquisition, and actor collaboration to a “whole of value-chain” perspective in transitional economies by investigating a subsistence smallholder agricultural value-chain. It examines the relationships between EO and vertical knowledge acquisition and the role of value-chain collaboration. It also contributes to the understanding of entrepreneurship as an economic development tool by considering how EO moderates the effect of value-chain actor collaboration on acquiring market and consumer knowledge by subsistence upstream actors within value-chains. Data were collected through a survey of smallholder value-chain shifting from selling to local wet markets to selling to cattle collectors and traders and through a value-chain to retailers. The findings suggest that higher levels of EO by smallholders and SME agribusinesses enhance the acquisition of vertical knowledge such as market and consumer preference information throughout the value-chain, and interfirm collaboration positively moderates this relationship.

We analyze the endogenous choice of competition mode when asymmetric retailers engage in price discrimination and uniform pricing with upstream monopoly via a linear wholesale contract. In contrast to previous results, if the cost difference is sufficiently large between asymmetric retailers, choosing a price contract for the efficient retailer and choosing a quantity contract for the inefficient retailer are implemented under both price discrimination and uniform pricing rules, while Cournot competition is sustained if the cost difference is sufficiently small. Although similar endogenous choice of (a)symmetric competition in equilibrium can be achieved in both pricing rules, social welfare, producer and consumer surpluses are higher under price discrimination than under uniform pricing unless the cost difference is small.

Transboundary pollution often affects natural resources in downstream countries. The harmful impact of upstream pollution on agricultural land use has been scantily studied. This paper models transboundary pollution and argues that in the presence of international trade between contiguous countries the polluter may find it incentive-compatible to abate pollution at the source. In particular, if the trade prospects in the upstream country depend on crucial inputs imported from the downstream, which gets affected by effluents, then the free-riding problem with abatement goes away. Further, if the upstream country cares about the welfare of its workers more than the owners of capital it would unambiguously enforce pollution abatement for its firms.

The upstream sector of the Oil and Gas (O&G) industry is recognized by its capital-intensive projects and complex and hazardous associated recovery and production processes, thus susceptible for large and financially damaging accidents. In this context, to avoid the risk and impact of high expenses, O&G companies usually acquire insurance contracts. In practice, although the contract format is typically pre-specified, its parameter magnitudes can be adjusted aiming at maximizing the company total wealth. Therefore, this work proposes a holistic methodology to assess the optimal parameter specification of an insurance contract in the upstream sector of the O&G industry. A non-convex stochastic optimization problem is constructed aiming at maximizing a risk-adjusted measure of the policyholder total wealth. The modeling takes into account the uncertainty on the financial loss of an accident by making use of the safety barriers and precursor information framework. The non-convex optimization problem is cast as an equivalent mixed-integer linear programming problem by combining the scenario-based representation approach with a set of binary reformulation procedures. We illustrate the applicability of the proposed methodology with a set of numerical experiments. In a nutshell, we found that the proposed parameter specification methodology resulted in greater predictability when compared to two quantile-based specification policies and an uninsured company. In fact, the second best policy presented a standard deviation 103% higher than the proposed methodology. Furthermore, the model also provided greater protection against extreme events, since the second best policy presented a Conditional Value-at-Risk 41% higher than the proposed methodology.

The hydrocarbon supply chain (HCSC) is a significant part of the world's energy sector. The energy market has experienced erratic behavior over the last few years results in financial risks such as exceeding certain limits of the budget or not achieving the desired levels of cash in-flow, i.e., revenue. In this work, robust optimization and multi-objective mathematical programming are used to develop a model that eliminates or at least mitigates the impact of uncertain market behavior. Robust optimization provides tactical plans that are feasible and robust over market scenarios. The model assesses the trade-offs between alternatives and guides the decision-maker towards the effective management of the HCSC. The economic objectives are to minimize total cost and maximize revenue, while the non-economic objective is to minimize the depletion rate. The model considers the environmental aspect by limiting the emission of CO2 and the sustainability aspect by reducing the depletion rate of natural resources. Uncertain behavior of the oil market is modeled on scenario representation. A case study based on real data from Saudi Arabia HCSC is provided to demonstrate the model's practicality, and a sensitivity analysis is conducted to provide some managerial insights. The results indicate that Saudi Arabia can cover its entire expenditure, break-even-point, by producing oil at 7.18 MMbbld and gas at 3,543.48 MMcftd. Besides, the robust approach provides a preferred plan with the highest cash inflow and the lowest sustainability over other approaches, e.g., deterministic, stochastic, and risk-based. The differences show that the robust model increases oil production to compensate for the variability of the scenario.

This paper presents a branch-and-cut algorithm and an adaptive large neighborhood search (ALNS) heuristic for the periodic supply vessel planning problem (PSVPP) arising in the upstream offshore petroleum logistics chain. Platform supply vessels support the offshore oil and gas exploration and production activities by transporting all the necessary material and equipment back and forth between offshore units and an onshore supply base according to a delivery schedule. The PSVPP consists of solving a periodic vehicle routing problem and simultaneously determining an optimal fleet size and mix of heterogeneous offshore supply vessels, their weekly routes and schedules for servicing the offshore oil and gas installations, and the berth allocations at the supply base. The branch-and-cut algorithm considers a reduced formulation for the problem which performs much better than the complete one, and easily finds optimal solutions for the smaller and most of the clustered instances. The ALNS heuristic contains new features which include multiple starts and spaced local searches. These algorithms were tested on instances with up to 79 offshore units, providing better results than the best available.

Since 2016, Canada’s federal government has pledged to factor in upstream emissions during the environmental impact assessment of fossil fuel energy projects. The upstream emissions attributable to a proposed project could be compared against a rejection threshold—a maximum permissible level of emissions—or the firm could be mandated to offset the attributed emissions. We adopt a cooperative game-theoretic model and propose the nucleolus mechanism to apportion upstream emission responsibilities in a fossil fuel supply chain, represented by a directed tree, wherein the nodes correspond to various entities in the supply chain such as extractors, distributors, refineries, and end consumers. The nucleolus allocation avoids the distortionary effects of double counting and exhibits a certain consistency property that is especially important in a regulatory context wherein fossil fuel supply chains span multiple legal jurisdictions. We develop a polynomial-time algorithm to compute the nucleolus and further prove that it arises as the unique subgame perfect equilibrium allocation of a noncooperative game induced by two easily stated and verifiable policies, thereby providing an implementation framework. We then demonstrate the strong Nash stability of the nucleolus mechanism subject to the two policies, study its sensitivity to parameter changes, and characterize it on the basis of fairness considerations. Furthermore, under the common assumption that the emissions allocated to a firm and the resulting financial penalties do not impact the revenues from the firm’s core operations, we also provide lower-bound guarantees on the welfare gains it delivers to firms in the fossil fuel supply chain and on the incentives it offers such firms to adopt emission abatement technologies. Finally, we contextualize our discussion with a case study on a proposed expansion of the Trans Mountain pipeline in Western Canada. This paper was accepted by Chung Piaw Teo, optimization.

Oil and gas industries are facing several challenges and issues in data processing and handling. Large amount of data bank is generated with various techniques and processes. The proper technical analysis of this database is to be carried out to improve performance of oil and gas industries. This paper provides a comprehensive state-of-art review in the field of machine learning and artificial intelligence to solve oil and gas industry problems. It also narrates the various types of machine learning and artificial intelligence techniques which can be used for data processing and interpretation in different sectors of upstream oil and gas industries. The achievements and developments promise the benefits of machine learning and artificial intelligence techniques towards large data storage capabilities and high efficiency of numerical calculations. In this paper a summary of various researchers work on machine learning and artificial intelligence applications and limitations is showcased for upstream and sectors of oil and gas industry. The existence of this extensive intelligent system could really eliminate the risk factor and cost of maintenance. The development and progress using this emerging technologies have become smart and makes the judgement procedure easy and straightforward. The study is useful to access intelligence of different machine learning methods to declare its application for distinct task in oil and gas sector.

Arundhati C. Khandkar and Ashok C. Khandkar, Swimming Upstream: Laxmanshastri Joshi and the Evolution of Modern India. New Delhi: Oxford University Press, 2019, xxiv + 193 pp., ₹1,195, ISBN: 9780199495153 (Hardback).

Subarnarekha River lies in the vicinity to the Ranchi mega lineament zone of Jharkhand State. This river links the Tamar Porapahar shear zone and North Singhbhum shear zone. The Hundru falls is the sudden and abrupt drop of elevation (longitudinal profile) of upstream of river Subarnarekha. The basic aim of this paper is to assess the Hundru falls as a perfect citation of an upstream knick point in Indian context. This paper covers the knick point formation of upstream of the Subarnarekha river. This upper catchment is more diversified in the terms of metamorphic and igneous rocks. This zone has crossed a long path with diversified lithospheric adjustment with epirogenic upliftment.

Aging workers in manufacturing are at greater risk of workforce departure than in other sectors. Workers in manufacturing have a variety of job types. Some jobs require traditional kinds of intensive manual labor, but new technology now requires many workers to operate automated machines from computer workstations, resulting in different physical demands from traditional production jobs that can nonetheless contribute to musculoskeletal strain and decreased functional capacity. Musculoskeletal health (MSH) and perceived work ability (PWA) are relevant to departure decisions, yet studies rarely model these constructs simultaneously. We used the job demands-resources model to evaluate job/personal demands and resources as antecedents of MSH and PWA, and examine both as mediators of departure. Workers from six U.S. manufacturers completed surveys (N = 758). Most were white, male, married, and middle-aged (M = 47.2 years). Hypotheses were tested using multiple linear regression and structural equation modeling. MSH and PWA were modeled as latent variables, and all others as observed variables. MSH and PWA were impacted by different demands and resources. Job demands (computer-based) and personal resources (sleep quality, leisure-time walking) predicted MSH, and job resources (supervisor support) and personal resources (sleep surplus) predicted PWA. MSH mediated relations of computer-based job demands, sleep quality, and leisure-time walking with PWA. MSH and PWA were unrelated to departure, likely due to sampling limitations. Identifying upstream causes of MSH and PWA provides primary preventative points of intervention – such as reducing job demands and offering needed resources – that may improve the health and functioning of aging workers.

Poverty affects child health and well-being in short- and long-term ways, directly and indirectly influencing a range of health outcomes through linked social and environmental challenges. Given these links, pediatricians have long advocated for poverty reduction in both clinical settings and society. Pediatricians and others who work in pediatric settings are well-suited to address poverty given frequent touchpoints with children and families and the trust that develops over repeated encounters. Many pediatricians also recognize the need for cross-sector engagement, mobilization, and innovation in building larger collaborative efforts to combat the harmful effects of poverty. A range of methods, like co-design, community organizing, and community-engaged quality improvement, are necessary to achieve measurable progress. Moreover, advancing meaningful representation and inclusion of those from underrepresented racial and ethnic minority groups will augment efforts to address poverty within and equity across communities. Such methods promote and strengthen key clinical-community partnerships poised to address poverty's upstream root causes and its harmful consequences downstream. This article focuses on those clinical-community intersections and cross-sector, multi-disciplinary programs like Medical-Legal Partnerships, Medical-Financial Partnerships, clinic-based food pantries, and embedded behavioral health services. Such programs and partnerships increase access to services difficult for children living in poverty to obtain. Partnerships can also broaden to include community-wide learning networks and asset-building coalitions, poised to accelerate meaningful change. Pediatricians and allied professionals can play an active role; they can convene, catalyze, partner, and mobilize to create solutions designed to mitigate the harmful effects of poverty on child health.

The Dujiangyan Project, located at the junction of the upstream of the Minjiang River and Chengdu Plain, Sichuan Province, China, is an irrigation system project as important as the Great Wall in the history of China. Without dam structures, this project has been continuously playing its crucial role in diverting water for irrigation, separating sediments, and controlling flood for 2275 years. In this study, the predicaments of the Dujiangyan Project under the background of rapid urbanization and social economic development were summarized by conducting the field research and using the Indicators of Hydrological alteration (IHA) method: excessive diversion of water, disruption of hydrological pulses, erosion and deposition imbalance and conflicts between power generation and water supply. These contradictions have led to the weakening of the function of automatic water diversion and sand removal in the Dujiangyan Project. Considering the influence of climate change and strong human activities, we pointed out the challenges faced by the millennium ancient weir in balancing human and environmental water usage and project operation and management based on the simulation results of the hydrological model. The corresponding suggestions about strengthening agricultural water saving, generating artificial flood peak were provided to protect and continue to maintain the function of the Dujiangyan Project.

Producción Científica, River fragmentation and alterations in flow and thermal regimes are the main stressors affecting migrating fish, which could be aggravated by climate change and increasing water demand. To assess these impacts and define mitigation measures, it is vital to understand fish movement patterns and the environmental variables affecting them. This study presents a long-term (1995–2019) analysis of upstream migration patterns of anadromous and potamodromous brown trout in the lower River Bidasoa (Spain). For this, captures in a monitoring station were analyzed using Survival Analysis and Random Forest techniques. Results showed that most upstream movements of potamodromous trout occurred in October–December, whereas in June–July for anadromous trout, although with differences regarding sex and size. Both, fish numbers and dates varied over time and were related to the environmental conditions, with different influence on each ecotype. The information provided from comparative studies can be used as a basis to develop adaptive management strategies to ensure freshwater species conservation. Moreover, studies in the southern distribution range can be crucial under climate warming scenarios, where species are expected to shift coldwards., Proyecto de innovación docente de la Universidad de Valladolid (PIF-UVa 2017), Ministerio de Ciencia, Innovación y Universidades (grant PTQ2018-010162), Publicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCLE

OPLC (optical fiber composite low-voltage cable) technology is a common field of communication and power electronics technology, and it is an important means to realizing the energy Internet and the integration of four networks. As an infrastructure sharing technology, OPLC technology will fundamentally and substantially promote the sustainable development of China’s economy and environment. Taking typical OPLC projects in China as an example, the direct energy consumption of these projects is calculated by the life-cycle cost (LCC) analysis method and then compared with traditional projects that use only power technology or optical fiber. Based on the direct consumption of the project, the interaction between the intermediate sector and the total output variable under the traditional technology and OPLC technology was explored and compared by using the input-output (I-O) model and the structural decomposition model (SDA). The results showed that in 2015, technology substitution weakened the influence of 86% of industries on the upstream industry and weakened the demand sensitivity of 90% of industries to the downstream industry. In 2017, technology substitution reduced the industry’s influence over 86% of upstream industries. Short-term technology replacement will not increase the positive influence of each industry on the upstream industry, thus resulting in a negative impact of technology substitution cost. However, that negative impact will gradually weaken over time. After technology replacement, the total added value of 20 industries increased from 2015 to 2017.

The location problem of Bundling Hubs (BHs) remains a contentious issue for efficient shared transportation systems. In this respect, the strategic configuration of BHs plays a crucial role in saving supply costs, covering demand, and minimizing the external effects of Shared Passenger and Freight Public Transportation (SPFPT). As urban areas become crowded, they show a significant increase in congestion and transport demand. Thus, sites where logistic operations, sales, or services are likely to occur, imply the final customers whose transport demand is a key factor that could affect cargo distribution using SPFPT systems. Since each BH should help efficiently to satisfy the transport demand of allocated customers, they would not play their key role if such factor of demand is not involved upstream in the long-term scheduling horizon. This paper focuses on locating BHs, using a Hybrid Robust Machine Learning-Heuristic Algorithm (HR-MLHA), among established ones and existing demand nodes while assessing a dynamic process so that the configured BH network is robust. The feature of robustness is supported by a robust command to keep BHs attractive and demand-responsive for the long-term in dynamic environments, i.e., the cities. To reduce complexity, the conceptual and computational approaches are structured in two main axes. The first axis includes a machine-learning-based zoning approach that helps with targeting the implementation area and assessing demand behavior. The second axis presents a mathematical model of the capacitated two-echelon BH location problem. When looking across the two-echelon location process, we aim at conducting dynamic location analysis using both current and predicted demand. In order to validate our approach, a set of benchmarks has been performed comparing with existing heuristics and using a whole package of experimental and real-life instances. The experimental results provided through the proposed approach have allowed valuable insights into successfully implementing our methodology.

This article shares choices made as part of an introductory decoloniality curriculum in a non-clinical community psychology M.A./PhD program where the authors are faculty members. We focus on the basics of decoloniality and decolonial pedagogies in two first-year foundational psychology courses: one course on implications of decoloniality for studying differing psychological paradigms, ontologies, and epistemologies, particularly relational ontologies that might reframe community environments, and another course on implications of decoloniality for post-humanist and indigenous qualitative research methodologies. We present currently emerging forms of theory, content, pedagogy, dialogue, artivism, and methodology in process in our work, as well as responses from students and our own reflections.

•Provisions in many data protection laws require a legal basis, or at the very least safeguards, for significant, solely automated decisions; Article 22 of the GDPR is the most notable. •Little attention has been paid to Article 22 in light of decision-making processes with multiple stages, potentially both manual and automated, and which together might impact upon decision subjects in different ways. •Using stylised examples grounded in real-world systems, we raise five distinct complications relating to interpreting Article 22 in the context of such multi-stage profiling systems. •These are: the potential for selective automation on subsets of data subjects despite generally adequate human input; the ambiguity around where to locate the decision itself; whether ‘significance’ should be interpreted in terms of any potential effects or only selectively in terms of realised effects; the potential for upstream automation processes to foreclose downstream outcomes despite human input; and that a focus on the final step may distract from the status and importance of upstream processes. •We argue that the nature of these challenges will make it difficult for courts or regulators to distil a set of clear, fair and consistent interpretations for many realistic contexts.

Apart from consumption as fresh produce and considering its health benefits, there is a huge demand for by-products of organic pumpkin in the domestic and global market. The value-added products of organic pumpkins like seeds, bread, biscuits, cakes and juice have an opportunity to capture the market share in the snack food industry. The paper aims to perform a value chain analysis of organic pumpkins in India. This study presents the results of the value chain analysis of organic pumpkin in three aspects, i.e. mapping of the chain, upgrading strategy and governance structure. Primary data is collected through a structured questionnaire from key chain actors (farmers, wholesalers and retailers). Descriptive statistics and one-way ANOVA is used to analyse the data. The study showed that the value chain of organic pumpkin is upstream in nature and no separate marketing channel is maintained for organic produces. The major function of value addition like packaging, labelling and processing of organic pumpkin is missing, and the chain has a weak governance structure. The study will help policymakers and key actors to identify the various gaps and lags in the existing chain and frame a strong value chain model for the flow of organic products from producer to consumer.

Companies manage their product portfolios to create value. Products and associated materials are important flows that link supply chains entities from upstream to downstream. Product deletion is a ...

In Southeast Asia, access to improved forages remains a challenge for smallholder farmers and limits livestock production. We compared seed exchange networks supporting two contrasting livestock production systems to identify bottlenecks in seed availability and determine the influences of the market, institutions, and cultural context of seed exchange, using interview-based methods for ‘seed tracing’ and network analysis. Government agencies were the primary sources of high-quality genetic materials, with secondary diffusion in the Philippines dairy case being dominated by key individuals in active cooperatives. In the Vietnamese beef-oriented production context, farmer to farmer dissemination was more substantial. In both cases, formal actors dominated where botanical seed was exchanged, while farmers frequently exchanged vegetatively propagated materials among themselves. To improve access to forage seed in these contexts, government agencies and development actors should coordinate quality seed production upstream while supporting the creation of appropriate training, structures, and incentives for seed exchange network improvement downstream.

Purpose The purpose of this paper is to examine how upstream social marketing can benefit from using social media commentary to identify cognitive biases. Using reactions to leading media/news publications/articles related to climate and energy policy in Australia, this paper aims to understand underlying community cognitive biases and their reasonings. Design/methodology/approach Social listening was used to gather community commentary about climate and energy policy in Australia. This allowed the coding of natural language data to determine underlying cognitive biases inherent in the community. In all, 2,700 Facebook comments were collected from 27 news articles dated between January 2018 and March 2020 using exportcomments.com. Team coding was used to ensure consistency in interpretation. Findings Nine key cognitive bias were noted, including, pessimism, just-world, confirmation, optimum, curse of knowledge, Dunning–Kruger, self-serving, concision and converge biases. Additionally, the authors report on the interactive nature of these biases. Right-leaning audiences are perceived to be willfully uninformed and motivated by self-interest; centric audiences want solutions based on common-sense for the common good; and left-leaning supporters of progressive climate change policy are typically pessimistic about the future of climate and energy policy in Australia. Impacts of powerful media organization shaping biases are also explored. Research limitations/implications Through a greater understanding of the types of cognitive biases, policy-makers are able to better design and execute influential upstream social marketing campaigns. Originality/value The study demonstrates that observing cognitive biases through social listening can assist upstream social marketing understand community biases and underlying reasonings towards climate and energy policy.

Throughout the project life cycle, project-based firms (PBFs) rely on various agents, such as subcontractors and consultants, to carry out activities on their behalf. Although a considerable body of literature has discussed when and how PBFs use agents, little is known about the nature of the agency relationships between PBFs acting as principals and their agents and how these relationships may be associated with the practices used by PBFs to govern their agents’ behaviour. The purpose of this conceptual study is to provide further insight into the characteristics of PBFs’ agency relationships and to identify and describe alternative approaches used for managing them. Our analysis reveals that PBFs’ agency relationships differ significantly regarding actor goals, risks, and availability of information across the project life cycle. Based on our findings, we propose a typology of the upstream agency relationships of a PBF consisting of four ideal types: operational, trustful, volatile, and strategic agency relationships. We argue that the development of agency relationships is a dynamic process which is contingent to the temporal orientation of the principal and the agent as well as congruence of goals between the principal and the agent. publishedVersion

This paper explores the effects of cooperation between rail and air infrastructures in setting per-passenger fees prior to competition among airlines and high-speed rail (HSR) in a transport network. It is shown that, for a sufficiently low degree of substitution, cooperation results in lower fees and greater HSR traffic than under competition. Besides, it leads to more connecting passengers. An empirical application allows for a quantitative assessment of cooperation. Gains to passengers and operators are sizeable when cooperation either involves all infrastructure managers or the rail and the hub airport managers. Welfare gains are in the range of 10.4–11.1%. Our contribution offers an ex-ante analysis about the benefits of intermodal cooperation at the upstream level.