Among the administrative techniques proposed by the New Public Management, the implementation of performance contracting instruments stands out. We discuss the application of this context in Minas ...Gerais, with the establishment of the Results Agreement from 2004 to 2014, focusing on indicators of effectiveness of public policies, definition of goals that reflect the contribution of teams and the payment of Productivity Award; and, starting in 2015, with the adoption of the Citizens Pact, seeking to simplify and incorporate institutionalized participatory processes, especially the Regional Forums of Government, but eliminating the figure of the Productivity Award.
The COVID-19 pandemic unveils unforeseen and unprecedented fragilities in supply chains (SC). A primary stressor of SCs and their subsequent shocks derives from disruption propagation (i.e., the ...ripple effect) through related networks. In this paper, we conceptualize current state and future research directions on the ripple effect for pandemic context. We scrutinize the existing OR (Operational Research) studies published in international journals dealing with disruption propagation and structural dynamics in SCs. Our study pursues two major contributions in relation to two research questions. First, we collate state-of-the-art research on disruption propagation in SCs and identify a methodical taxonomy along with theories displaying their value and applications for coping with the impacts of pandemics on SCs. Second, we reveal and systemize managerial insights from theory used for operating (adapting) amid a pandemic and during times of recovery, along with becoming more resistant to future pandemics. Streamlining the literature allowed us to reveal several new research tensions and novel categorizations and classifications. The outcomes of our study show that methodical contributions and the resulting managerial insights can be categorized into three levels, i.e., network, process, and control. Our analysis reveals that adaptation capabilities play the most crucial role in managing the SCs under pandemic disruptions. Our findings depict how the existing OR methods can help coping with the ripple effect at five pandemic stages (i.e., Anticipation; Early Detection; Containment; Control and Mitigation; and Elimination) following the WHO classification. The outcomes and findings of our study can be used by industry and researchers alike to progress the decision-support systems guiding SCs amid the COVID-19 pandemic and toward recovery. Suggestions for future research directions are offered and discussed.
The fourth industrial revolution we currently witness changes the role of humans in operations systems. Although automation and assistance technologies are becoming more prevalent in production and ...logistics, there is consensus that humans will remain an essential part of operations systems. Nevertheless, human factors are still underrepresented in this research stream resulting in an important research and application gap. This article first exposes this gap by presenting the results of a focused content analysis of earlier research on Industry 4.0. To contribute to closing this gap, it then develops a conceptual framework that integrates several key concepts from the human factors engineering discipline that are important in the context of Industry 4.0 and that should thus be considered in future research in this area. The framework can be used in research and development to systematically consider human factors in Industry 4.0 designs and implementations. This enables the analysis of changing demands for humans in Industry 4.0 environments and contributes towards a successful digital transformation that avoid the pitfalls of innovation performed without attention to human factors. The paper concludes with highlighting future research directions on human factors in Industry 4.0 as well as managerial implications for successful applications in practice.
Because of uncertainty in customer demand and lack of understanding in customer reactions to price changes, it is a challenge for many companies, such as manufacturers and retailers, to match supply ...and demand. Most of the models in the operations literature, however, have focused on the case in which the underlying customer demand information is known a priori, which is not true in many applications. In “Coordinating Pricing and Inventory Replenishment with Nonparametric Demand Learning,” B. Chen, X. Chao, and H. Ahn develop a data-driven algorithm for pricing and inventory decisions that learns the demand and customer information from sales data on the fly, and they show that the profit generated from the algorithm converges to the clairvoyant optimal profit at the quickest possible rate.
We consider a firm (e.g., retailer) selling a single nonperishable product over a finite-period planning horizon. Demand in each period is stochastic and price sensitive, and unsatisfied demands are backlogged. At the beginning of each period, the firm determines its selling price and inventory replenishment quantity with the objective of maximizing total profit, but it knows neither the average demand (as a function of price) nor the distribution of demand uncertainty a priori; hence, it has to make pricing and ordering decisions based on observed demand data. We propose a nonparametric, data-driven algorithm that learns about the demand on the fly and, concurrently, applies learned information to make replenishment and pricing decisions. The algorithm integrates learning and action in a sense that the firm actively experiments on pricing and inventory levels to collect demand information with minimum profit loss. Besides convergence of optimal policies, we show that the regret of the algorithm, defined as the average profit loss compared with that of the optimal solution had the firm known the underlying demand information, vanishes at the fastest possible rate as the planning horizon increases.
•Piezoresistivity of cement-based sensors is affected by materials, loading, measurements and environmental conditions.•Both conductive and non-conductive phases influence piezoresistivity of sensors ...and there is optimal conductor content.•Manufacturing procedure significantly affects the dispersion of conductors and microstructure of cement-based sensors.•Increased temperature and humidity can enhance piezoresistivity of sensors but decrease it when certain limits are exceeded.
Cement-based sensors are increasingly used in smart concrete to self-sense and monitor the damages and cracks through the measurements of concrete electrical resistivity. The fundamental concepts, key components, manufacturing process, piezoresistivity measurements, and primary applications of cement-based sensors are reviewed in this paper. Various materials, mechanical and environmental factors affecting concrete piezoresistive properties are explicated. Some contradictory results from different studies are reported and discussed. Future perspectives of piezoresistive cement-based sensors are also delineated. The review reveals that there is an optimal conductor content, below which the sensor would perform more like plain concrete with high resistivity and low sensitivity, while excessively higher than which, the dispersion of the conductive phase could become difficult, thus increasing resistivity. The manufacturing process, such as the dispersion method of conductors and curing condition, plays a significant role in conductor distribution, matrix density and pore structure of the sensors, which, together with rheology of the sensor composite, consequently alters the piezoresistive properties of the sensors. In addition to responding to mechanical loading, cement-based piezoresistive sensor also has a great potential for monitoring behaviour of concrete under freeze-thaw cycling. It is expected that this review will provide not only an orientation for new researchers to explore and engage in related studies but also an insight for experienced researchers to perform transformational examinations into cement-based piezoresistive sensors.
This research uses sensemaking theory to explore how emerging blockchain technology may transform supply chains. We investigate three research questions (RQs): What are blockchain technology's ...perceived benefits to supply chains, where are disruptions mostly likely to occur and what are the potential challenges to further blockchain diffusion? We conducted in-depth interviews with 14 supply chain experts. Cognitive mapping and narrative analysis were deployed as the two main data analysis techniques to aid our understanding and evaluation of people's cognitive complexity in making sense of blockchain technology. We found that individual experts developed different cognitive structures within their own sensemaking processes. After merging individual cognitive maps into a strategic map, we identified several themes and central concepts that then allowed us to explore potential answers to the three RQs. Our study is among the very few to date to explicitly explore how blockchains may transform supply chain practices. Using the sensemaking approach afforded a deeper understanding of how senior executives diagnose the symptoms evident from blockchains and develop assumptions, expectations and knowledge of the technology, which will then shape their future actions regarding its utilisation. We demonstrate the usefulness of sensemaking theory as an alternative lens in investigating contemporary supply chain phenomena such as blockchains. Bringing sensemaking theory to this discipline in particular enriches emerging behavioural operations research. Our contributions also lie in extending the theories of prospective sensemaking and adding further insights to the stream of technology adoption studies.
•We investigate how blockchains may transform supply chains.•We adopt sensemaking theory to gauge foresights via expert interviews.•We identify the perceived benefits of blockchains to supply chains.•We establish potential areas where blockchains may penetrate supply chains.•We elucidate the challenges of blockchain technology's further diffusion into supply chains.
In many systems with limited service capacity, customers must wait in a queue for service. When customers cannot observe the queue, how should a revenue-maximizing service provider convey information ...about wait times? In “Optimal Signaling Mechanisms in Unobservable Queues,” D. Lingenbrink and K. Iyer study this problem and characterize the structure of the optimal signaling mechanism. To signal optimally, the service provider uses two possible signals, “short” and “long,” to tell customers the queue length is short when below a threshold and long when above it. For the specific case of linear waiting costs, the authors explicitly compute this threshold. Furthermore, they show that for an optimally chosen fixed service price, optimal signaling produces the same expected revenue as a pricing mechanism that sets prices based on the number of customers waiting. This suggests that in settings where one cannot dynamically update prices, signaling can be effective in generating revenue.
We consider the problem of optimal information sharing in an unobservable single-server queue offering service at a fixed price to a Poisson arrival of delay-sensitive customers. The service provider observes the queue and may share state information with arriving customers. The customers, who are Bayesian and strategic, incorporate this information into their beliefs before deciding whether to join the queue. We pose the following question: Which signaling mechanism should the service provider adopt to maximize her expected revenue? We formulate this problem as an infinite linear program in the queue’s steady-state distribution and establish that, in general, the optimal signaling mechanism requires the service provider to strategically conceal information in order to incentivize customers to join. In particular, we show that a binary signaling mechanism with a threshold structure is optimal. Finally, we prove that coupled with an optimal fixed price, the optimal signaling mechanism generates the same expected revenue as the optimal state-dependent pricing mechanism. This suggests that in settings where state-dependent pricing is infeasible, signaling can be effective in achieving the optimal revenue. Our work contributes to the literature on dynamic Bayesian persuasion and provides many interesting directions for extensions.
The importance of big data analytics–enabled dynamic capability has been at the forefront of research for information systems management, operations management, and strategic management community. ...Prior studies have reported on the influence of big data analytics–enabled dynamic capability (BDA) for improved organizational agility and organizational performance, but there has been a paucity of literature regarding the role of big data analytics–enabled dynamic capability in untangling the supply chain ambidexterity dilemma and organizational performance. To address these research gaps, this paper draws on the dynamic capability view of the organization under the contingent effect of environmental dynamism. We tested our research hypotheses using 281 surveys, gathered using a pre-tested questionnaire. Our results suggest that BDA has positive effects on improving supply chain agility (SCAG), supply chain adaptability (SCAD) and performance measures (cost performance and operational performance). However, we noted that hypotheses regarding the moderating effect of environmental dynamism (ED) on the paths joining BDA and SCAG/SCAD were not supported. To address these unexpected results, we conducted post hoc analysis to explain the rationale behind the insignificant moderating effects of ED on the paths joining BDA and SCAG/SCAD. We found that the effects of BDA on SCAG/SCAD were higher under intermediate levels of environmental dynamism but comparatively weak when the environmental dynamism is low or high. Hence, we can argue that big data analytics can help enhance supply chain agility, supply chain adaptability, and organizational performance, but these effects are contingent upon the level of environmental dynamism. Moreover, a non-linear, inverse U-shaped moderating effect of environmental dynamism exists. Collectively, these findings provide a theory-based understanding of the organizational level of usage of big data analytics and its effects on supply chain agility, supply chain adaptability, and organizational performance. Moreover, they further shape our understanding of how big data analytics–enabled dynamic capabilities yield differential results under the moderating effect of environmental dynamism. Hence, we believe that our results will be useful for managers who are highly optimistic about the usage of these emerging technologies and their effects on supply chain characteristics. Finally, we have outlined our study limitations and offered numerous research directions.
Nutritional value of black soldier fly Seok-Kian, Annita Yong; Mustafa, Saleem; Shapawi, Rossita ...
PloS one,
02/2022, Letnik:
17, Številka:
2
Journal Article
Recenzirano
Nutritional value of black soldier fly (Hermetia illucens) larvae (BSFL) processed by three different methods of treatment was compared. The resulting products were the spray-dried BSFL (SPR), ...oven-dried BSFL 1 (OVN1) and oven-dried BSFL 2 (OVN2). Proximate chemical composition, and profiles of amino acids, fatty acids, minerals, heavy metals, vitamins and nucleotides were analysed and compared. The tested BSFL meals were considered to have a good profile of essential amino acids (EAAs), with leucine, lysine, valine, and histidine being the dominant EAAs. Their content of saturated fatty acids exceeded that of the unsaturated fatty acids. Vitamins B1, B2, and C were also present in the samples. Minerals such as calcium, potassium, phosphorus, sodium, magnesium, zinc, iron, manganese and copper were found to be in adequate amounts in almost all the samples. Heavy metals in the BSFL meals were mostly below 1g kg.sup.-1 . Nucleotides such as inosine monophosphate and uridine monophosphate occurred in all the BSFL meals. Other nucleotides, including guanosine monophosphate, adenosine monophosphate, xanthosine monophosphate, and cytidine monophosphate were detected in either or both of SPR and OVN2. In general, the nutritional value of the BSFL meals tested in the present study was influenced by the method of processing.
This study aimed to evaluate the optimum plot size for the papaya crop by using the modified maximum curvature method under soil and climatic conditions of the Reconcavo Baiano. The experiment ...comprised a uniformity test using the CNPMF-L78 strain developed by Embrapa Mandioca and Fruticultura, planted at a spacing of 3 m x 2 m, with 16 central rows and 22 plants per row, totaling 352 plants and an area of 2,112 m.sup.2. The following parameters were evaluated: plant height and diameter; height of insertion of the first fruits; precocity; number of commercial fruits per plant; productivity; length, diameter, weight, firmness, internal cavity diameter, pulp thickness, and soluble fruit solids. Each plant was considered as a basic unit, with an area of 6 m.sup.2, thus making up 352 basic units whose adjacent units were combined to form 11 pre-established parcel arrangements with rectangular and row formats. The optimal plot size is seven plants perpendicular to the crop rows, that is, seven rows with one plant in each row, corresponding to the area of 42 m.sup.2, considering spacing of 3 m between rows and 2 m between papaya plants in the soil and climatic conditions of the Reconcavo Baiano. Key words: Carica papaya L., experimental precision, uniformity. Objetivou-se avaliar o tamanho otimo de parcela para a cultura do mamoeiro pelo metodo da maxima curvatura modificado sob condicoes edafoclimaticas do Reconcavo Baiano. O experimento constituiu-se de um ensaio de uniformidade, utilizando a linhagem CNPMF-L78, desenvolvida pela Embrapa Mandioca e Fruticultura, plantada no espacamento de 3 m x 2 m, consideradas como util as 16 fileiras centrais com 22 plantas por fileira, totalizando 352 plantas e area de 2.112 m.sup.2. Foram avaliados: altura e diametro das plantas; altura de insercao dos primeiros frutos; precocidade de colheita; numero de frutos comerciais por planta; produtividade; comprimento, diametro, peso, firmeza, diametro da cavidade interna, espessura da polpa e solidos soluveis dos frutos. Nas avaliacoes, cada planta foi considerada como uma unidade basica, area de 6 m.sup.2, perfazendo assim, 352 unidades basicas, cujas as adjacentes foram combinadas de modo a formar 11 arranjos de parcelas pre-estabelecidos com formatos retangulares e em fileiras. O tamanho otimo de parcela e de sete plantas, com sentido perpendicular as fileiras do cultivo, ou seja, sete fileiras com uma planta em cada fileira, correspondente a area de 42 m.sup.2, considerando espacamento de 3 m entre linhas e 2 m entre plantas de mamoeiro nas condicoes edafoclimaticas do Reconcavo Baiano. Palavras-chave: Carica papaya L., planejamento experimental, ensaio em branco.
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