Product Demand Research Articles

The Effect of Working Capital, Sales, and Cash Ratio on Profitability

This study aims to analyze the effect of working capital, sales, and cash ratio on profitability at PT Indofood CBP Sukses Makmur during 2016-2020, using secondary data from the company's financial statements and multiple linear regression methods with Eviews. In 2017, the company's net profit decreased due to costs associated with launching new products to compete in the market. Nevertheless, product demand continued to grow among local and international customers, leading to an increase in working capital for marketing efforts. This study uses quantitative data from the financial statements of PT Indofood Sukses Makmur, analyzed using multiple linear regression to test the effect of working capital, sales, and cash ratio on profitability. The results of the study indicate that working capital does not have a significant impact on profitability due to ineffective turnover, in line with previous studies by Meidiyustiani (2016) and others. Sales have a negative impact on profitability, with high sales not covering the increase in operating costs. The cash ratio has a positive impact on profitability, although the impact is not significant, indicating that cash management is important but not the main driver of profit. Overall, this study shows that efficient use of working capital and cost management are key factors in increasing profitability.

How can Dynamic Pricing Models be Successfully Implemented into Digital Marketplaces to Benefit SMEs in Kazakhstan?

​​The increased popularity of digital marketplaces caused many SMEs to start their online journey. However, the lack of systematisation and optimisation means that SMEs are often unproductive and do not fulfil their potential. This is worsened by the cost complexity of import-focused pricing, which is caused by local market conditions and the swift nature of digital marketplaces. The Kazakhstani market is rapidly developing; however, it is relatively unstable for SMEs. The price complexity issue can be solved by developing dynamic pricing models based on regional contexts. This study created an optimisation model with a macroeconomic focus through data analysis of key economic factors in Kazakhstan. The final dynamic pricing model focused on inflation, exchange rates and product demand.

Riders on the storm: How do firms navigate production and market conditions amid El Niño?

This paper investigates how heavy rainfalls resulting from the 2002–03 El Niño climate pattern affect Ecuadorian firms' production and market conditions. We show that affected firms' revenue productivity (TFP-R) and markups decrease. This is due to production efficiency losses (TFP-Q) and higher marginal costs of initially less efficient firms. Decreased product output prices in response to lower product demand explain the impact on initially more efficient firms. However, the shock neither affects market shares nor survival rates of initially less efficient firms. Consequently, the productivity distribution of Ecuador's industry is not affected by the shock. We also show a swift recovery of production and market demand in the immediate aftermath of the shock. Impacts in 2002–03 are like those of the 1997–98 rainfall shock. Differentiating firms by their TFP-R rather than their production efficiency indicates firms with better (worse) market positions can mitigate the negative impacts of the shock more (less).

Product transportation strategy in the presence of limited shipment capacity and purchase timing

ABSTRACT In maritime practice, shippers can order shipment capacity before knowing product demand and then transport those products via liner shipping (LS) after observing demand information, or shippers can transport them when needed via tramp shipping (TS) without pre-ordering shipment. We develop a game-theoretic model to analyse these two transportation modes, LS and TS, in the presence or absence of demand and supply shocks such as those occurring in a pandemic. Interestingly, when vessels have a sufficiently small shipment capacity, the shipper prefers LS (TS) when market uncertainty is high (low) if the following is true: (a) the market size is moderate and there are no such shocks, or (b) the market is not sufficiently large in the case of shocks. This conclusion contradicts the naïve belief that the shipper prefers LS (TS) in the case of low (high) market uncertainty. Additionally, when the market is sufficiently large, the shipper prefers TS only if dead freight rate is low and the tramp vessel’s shipment capacity is moderately greater than that of LS. It follows that, due to high freight charges or low profit, the TS mode may not be the shipper’s best choice, even if the transportation demand is very large.

Product Demand Forecasting For Inventory Management with Freight Transportation Services Index Using Advanced Neural Networks Algorithm

Purpose: Accurate demand forecasting is critical for optimizing inventory management, improving customer satisfaction, and maximizing profitability in the retail sector. Traditional forecasting models predominantly utilize micro-level variables, such as historical sales data and promotional activities, often neglecting the influence of macroeconomic conditions. Materials and Methods: This study addresses this gap by integrating Freight Transportation Services Index (TSI) which is an indicator for overall economic health with time series data of retail product sales. Utilizing an advanced neural networks model, we demonstrate that incorporating macroeconomic variables significantly enhances the model's predictive accuracy and explanatory power. Findings: The results reveal that the model with the TSI index outperforms conventional models, highlighting its potential for practical application in the industry. Implications to Theory, Practice and Policy: This approach offers a more comprehensive understanding of demand dynamics, enabling businesses to make more informed decisions, adapt to market fluctuations, and maintain a competitive edge.

The Influence of Artificial Intelligence on the Automation of Processes in Electronic Commerce

This study explores the transformative impact of Artificial Intelligence (AI) on automating business processes in electronic commerce (e-commerce), with a focus on enhancing efficiency and customer experience. The research employs Deep Learning (DL) and Machine Learning (ML) as primary analytical tools to process and analyze data from e-commerce transaction records and customers’ browsing histories. Techniques such as data preprocessing, normalization, sentiment analysis, and advanced predictive models using Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Support Vector Machines (SVMs) are utilized. Data collection was conducted using web scraping tools like Beautiful Soup and Scrapy, along with APIs from Amazon and Google. The application of AI in e-commerce has led to significant improvements in inventory control, fraud prevention, and customer relations. ML algorithms have enhanced the estimation of product demand and personalized customer interactions, while DL has strengthened product recommendation systems and fraud detection mechanisms. The findings indicate that AI contributes to a more secure, faster, and smarter operational environment in e-commerce. This research highlights the substantial benefits and broad potential of AI in optimizing e-commerce operations, demonstrating that the integration of advanced AI technologies not only streamlines transactions but also reinforces platforms against fraudulent activities.

International operations and corporate R&D investment: Evidence from China.

This paper presents an examination of the relationship between international operations and corporate R&D investment. Using a large sample of Chinese listed firms for the 2009-2022 period and the ordinary least squares method, we find that international operations have a positive effect on corporate R&D investment. The finding remains valid after a battery of robustness tests. Mechanism tests show that international operations increase corporate R&D investment by diversifying product demand instead of increasing firms' international knowledge acquisition. This paper provides new evidence on the role of international operations in innovation activities.

Partial information sharing in supply chains with ARMA demand

AbstractIn this paper we suggest a novel mechanism for information sharing that allows a retailer to control the amount of shared information, and thus to limit information leakage, while still assisting the supplier to make better‐informed decisions and improve the overall efficiency of the supply chain. The control of the amount of leaked information facilitates information sharing because, absent such control, a retailer may refrain from sharing information due to the concern of information leakage. Specifically, we analyze a supply chain in which a retailer observes Autoregressive Moving Average (ARMA) demand for a single product where all players use the myopic order‐up‐to policy for determining their orders. We introduce a new class of information sharing arrangements, coined partial‐information shock (PaIS) sharing. This new class of information sharing agreements extends the previously studied mechanisms of demand sharing and full‐information shock sharing. We demonstrate that the retailer can construct a PaIS sharing arrangement that allows for an intermediate level of information sharing while simultaneously controlling the amount of leakage. We characterize when one PaIS arrangement will be more valuable to the supplier than another. We conclude with a numerical study that highlights that there does not necessarily need to be a tradeoff between the supplier having a better forecast and the retailer experiencing a higher level of leakage.

Does Privatization improve Corporate Governance and Profitability? Evidence from Cement Company of Northern Nigeria

The paper study how Privatization improves Corporate Governance and Profitability of Cement Company of Northern Nigeria. Data was collected from secondary sources, and the statistical tools employed in the Methodology were descriptive statistics and OLS regressions. The study aimed at bridging literature gap on studies that relate corporate governance and privatization policy in Nigeria. The results suggest that, The result suggest that, the company has lower market capitalization, private sector and foreign investors have concentrated ownership, bigger board size, lower percentage of executive directors and higher percentage of non-executive directors, Board chairmen were not the chief executives and chairmen audit committees were non-executive directors, lower workforce, higher percentage of management staff small percentage of non-management staff, lower profitability, products demand depended on government capital projects, The Company purchased 5MW power plant in 1991, macro-economic challenges such as devaluation of naira, energy sector crisis, foreign exchange rate, inflation, trade liberalization, inconsistent stabilization policies, political instability and banks’ strikes and weak private sector. Inferential result reveals that, has state ownership, percentage of management staff, percentage of non-management staff and privatization have positive and significant relationship with profitability. However, minority ownership has a negative and significant relationship with profitability. Based on these findings, the researcher arrived at the conclusion that, Corporate governance has significant impacts on profitability of Cement Company of Northern Nigerian. Even though, unfavourable macroeconomic environment militated against its efficiency. The study recommends that, government needs to introduce macroeconomic stabilization measures that will improve effective demand of cement products particularly with the problem of withdrawal of fuel subsidy in the economy. The company should, as a matter of necessity, design strategies that will; create international market opportunities, enhance security measures, cheap inputs, efficient financial and inventories management that will improve profitability post privatization.

Nutritional Strategies to Alleviate Stress and Improve Welfare in Dairy Ruminants.

Dairy ruminants provide a major part of the livestock and agriculture sectors. Due to the increase in world population and the subsequent increase in dairy product demands, the dairy sector has been intensified. Dairy farming intensification and the subsequent increase in animal nutritional demands and the increase in the average global temperature as well have subjected animals to various stress conditions that impact their health and welfare. Various management practices and nutritional strategies have been proposed and studied to alleviate these impacts, especially under heat stress, as well as during critical periods, like the transition period. Some of the nutritional interventions to cope with stress factors and ensure optimal health and production are the inclusion of functional fatty acids and amino acids and feed additives (minerals, prebiotics, probiotics, essential oils and herbs, phytobiotics, enzymes, etc.) that have been proven to regulate animals' metabolism and improve their antioxidant status and immune function. Thus, these nutritional strategies could be the key to ensuring optimum growth, milk production, and reproduction efficiency. This review summarizes and highlights key nutritional approaches to support the remarkable metabolic adaptations ruminants are facing during the transition period and to reduce heat stress effects and evaluate their beneficial effects on animal physiology, performance, health, as well as welfare.

Designing green logistics networks under carbon tax policy: Post-COVID condition

This paper proposes a fuzzy-based method for estimating demand in forward and reverse logistics networks (F&RLNs) subject to carbon pricing in the post-COVID era. We investigate the complex relationships between carbon prices, the reverse logistics network (RLN), and the ever-changing product demand by utilizing fuzzy inference systems (FIS) capabilities. The case study from Mexico confirms the effectiveness of the proposed technique. The findings demonstrate the precision and predictive power of our proposed FIS-based method and show how well it can predict the number of items in demand and the number of goods that will be returned and subject to carbon taxation in the post-COVID era. The results illustrate the significant impact that carbon pricing has on the RLN and the associated product demand. For logistics managers seeking to make informed decisions about the establishment and operation of forward and RLNs within the carbon pricing paradigm, this empirical data provides insightful information in the post-COVID era.

Effects of Volcanic Tuff Use on the Rheological and Mechanical Properties of Self-Compacting Concrete

The rise in demand of concrete products has led to overexploitation of river sand the main fine aggregate in concrete resulting in major environmental degradation. As a result, researchers have focused their efforts on developing eco-friendly concrete using alternative renewable materials like volcanic tuff and other natural pozzolana types. This study therefore, aims at investigating the use of Kenyan, Kitengela volcanic tuff as a partial replacement of river sand in self-compacting concrete, and determining the effects it will have on the rheological and mechanical properties of the self-compacting concrete. The study involved partially replacing river sand with volcanic tuff in percentages of 0%, 2.5%, 5%, 7.5% and 10% and carrying out rheological tests (V-funnel test, L-box test, T-500 test and J-ring test) on fresh concrete and mechanical tests (compressive strength and tensile strength tests) on hardened self-compacting concrete on days 7, 14, and 28 to determine the effects of volcanic tuff on properties of both fresh and hardened self-compacting concrete. There was a general decrease in rheological properties (flow and passing abilities) of self-compacting concrete with increase in volcanic tuff percentage replacement from 0 % to 10%, with least flow and passing abilities recorded at 10% replacement. Similarly, increase in volcanic tuff percentage replacement led to decrease in both compressive and tensile strength of self-compacting concrete with lowest values recorded at 10% volcanic tuff replacement.

Analyzing the Problems of Agricultural Futures Market in China

The agriculture is a fundamental sector for the development of society, and agricultural products play a key role in the economy. The equilibrium of agricultural product supply and demand is intimately linked to societal steadiness and the welfare of individuals. Consequently, the efficient functioning of the market for agricultural products is vital for economic growth. Agricultural product manufacturing and sales face multiple hazards, such as climatic change, natural disasters, market fluctuations, etc. Agricultural futures serve as a financial tool for the agricultural products market, providing essential hedging and risk management functions. The establishment and development of the agriculture futures market enables farmers and agricultural companies to hedge against agricultural product price fluctuations, reducing business operation risks. This promotes market stability and contributes to the healthy development of the economy. Additionally, investors can participate in the agricultural futures market to obtain investment income through price fluctuations. The agricultural futures market plays a significant role for farmers, agricultural companies, and investors. Therefore, researching and exploring this market is of great theoretical and practical importance and necessity.

A modified bi-objective NSGA-II approach to sustainability in reconfiguration planning of dynamic cellular manufacturing systems

Manufacturing plant layouts are developed to facilitate optimal process flow. Modern manufacturing systems must meet present production demands and be adaptable to changes in process flow in the future. Dynamic Cellular Manufacturing Systems (DCMS) increase the flexibility of layouts by reconfiguring cell structure and equipment distribution, to effectively adjust part routings for optimal process flow. Frequent reconfiguring of plant layout may not always be feasible or economical, however, when new product releases are planned, reconfiguring the plant layout to optimise the work-flow may be extremely beneficial. This paper presents a Non-dominated Sorting Genetic Algorithm (NSGA-II) approach to solving a DCMS problem in a sustainable, and responsible manner. A bi-objective integer programming model was developed over multiple planning horizons with fluctuating product demands. This model aims to achieve sustainability by reducing the cost of production, mitigating the environmental impact of production, and minimise negative social impacts on labourers that work in such environments. A penalty function approach was used to enforce the model constraints during optimisation. This study details trade-offs between the economic factors of a DCMS, the environmental implications of reconfiguring such a system, and the social impacts of reconfigurations on the workforce.

Real-Time Monitoring of Human and Process Performance Parameters in Collaborative Assembly Systems using Multivariate Control Charts

With the rise in customized product demands, the production of small batches with a wide variety of products is becoming more common. A high degree of flexibility is required from operators to manage changes in volumes and products, which has led to the use of Human-Robot Collaboration (HRC) systems for custom manufacturing. However, this variety introduces complexity that affects production time, cost, and quality. To address this issue, multivariate control charts are used as diagnostic tools to evaluate the stability of several parameters related to both product/process and human well-being in HRC systems. These key parameters monitored include assembly time, quality control time, total defects, and operator stress, providing a more holistic view of system performance. Real-time monitoring of process performance along with human-related factors, which is rarely considered in statistical process control, provides comprehensive stability control over all customized product variants produced in the HRC system. The proposed approach includes defining the parameters to be monitored, constructing control charts, collecting data after product variant assembly, and verifying that the set of parameters is under control via control charts. This increases the system's responsiveness to both process inefficiencies and human well-being. The procedure can be automated by embedding control chart routines in the software of the HRC system or its digital twin, without adding additional tasks to the operator's workload. Its practicality and effectiveness are evidenced in custom electronic board assembly, highlighting its role in optimizing HRC system performance.

The impact of economic uncertainty on corporate trade credit policy: insights from the COVID-19 pandemic

ABSTRACT During the COVID-19 pandemic, firms exposed to the crisis faced simultaneous shocks to product demand and supply chains. As a result, they faced changing dynamics and greater uncertainty for trade credit for both suppliers and customers. Using regression analyses on quarterly data around the pandemic outbreak, we find that US non-financial firms demanded quicker payments from customers and faced shorter payment periods themselves during the pandemic. We also document that reduced trade credit was more pronounced for financially constrained firms and those with lower operating flexibility. Interestingly, government supplier firms’ trade credit remains unaffected by their COVID-19 exposure. These findings support the precautionary motives guiding firms’ trade credit policies in the face of economic uncertainty.

Product refurbishment in an imperfect production inventory system under carbon regulations: An interval type-2 fuzzy environment

This study develops an imperfect production inventory model focusing on the proper handling of imperfect products and addressing carbon emissions in different stages of a production process. The proposed inventory system consists of three stages: production, screening, and refurbishing. The produced products undergo a screening process, with perfect quality items being delivered to the primary market, while imperfect quality products are routed through a refurbishing process, subsequently sold in the secondary market. It is observed that in the existing literature on refurbished products, all such types of products have been sold at the end of the business period, this means that there is no continuous demand of refurbished product at the remaining time points of the business period which does not support the practical situation in a real business system. In this regards, our main objective in this study is consideration of continuous demand of refurbished products along with perfect ones. Again, we incorporate interval type-2 fuzzy uncertainty in both markets’ demand to better reflect market fluctuations introducing a new defuzzification method. In this framework, we evaluate the effectiveness of two emission regulatory strategies: carbon tax and carbon cap and trade policies. The findings of this study offer valuable insights into various aspects. Notably, our analysis reveals that if the difference between the primary and secondary markets’ demands reduces to a large extent, a negative impact on the profit is observed. It is also shown that an increase in demand for refurbished products allows for a higher permissible rate of imperfections in production. Comparing the outcomes under two emission regulations, we find that the cap and trade policy is beneficial from both economic and environmental perspectives. Additionally, it becomes evident that the manufacturer should carefully consider the duration of each inventory stage, as it leads to a significant increase in overall emissions. Regarding the uncertain nature of the market, it is observed that demand volatility in the secondary market negatively affects the profit.

Cutting-edge advances in alga Botryococcus for eco-friendly biofuels and high-value bioproducts — A critical review

Currently, natural product demand is increasing along with environmental sustainability and health-conscious lifestyle trends, in addition, sustainable energy use is also driving this demand. In recent years, algae based biorefineries have drawn a lot of attention. In this context, alga Botryococcus sp. has shown as a potential feedstock for a number of industries which includes cosmetics, nutraceuticals, medicines, and fuel. The alga Botryococcus produce a renewable and biodegradable alternative energy source in comparison to fossil fuels. The utilization of alga Botryococcus derived biodiesel can reduce the greenhouse gases emission during combustion, which lowers the carbon footprint overall. Understanding the most effective algae cultivation methods and production technologies is essential to fully utilize its potential in tackling the world's energy demands, uncertain climate change, and satisfying the increasing need for freshwater resources. Thus, this review demonstrates the importance of alga Botryococcus as a multifaceted source by thoroughly examining its properties. It also describes the opportunities and problems that Botryococcus faces moving forward in the context of a circular bioeconomy.

Commit on Effort or Sales? Value of Commitment in Live-streaming E-commerce

With rapid development of live-streaming e-commerce, an increasing number of firms are collaborating with live-streamers (e.g., online influencers and celebrities) to host online live-shows for selling their products. To reduce the firm’s risk and motivate it to stock more, live-streamers can commit a minimum sales volume and/or the effort devoted to attracting fans and promoting the upcoming live-show. In this article, we study the roles of such sales and effort commitments on the performance of a “supply chain” in which a seller sells its product via a live-streamer. Product demand at the live-show is random while depending on the live-streamer’s pre-show effort and the seller needs to decide the amount of inventory for sale at the live-show. We consider three scenarios, in which the live-streamer makes sales-only, effort-only, and hybrid commitments, and compare the decisions and profits of both parties. We show that the commitment on sales volume or effort is mutually beneficial to the seller and the live-streamer. Moreover, the hybrid commitment can motivate the seller to stock more inventory and induce more effort from the live-streamer compared to sales-only or effort-only commitment. The live-streamer always prefers the hybrid commitment whereas the seller may prefer the sales-only commitment, for example, when the penalty is at a medium level.

How the digital economy can contribute to green manufacturing efficiency

In response to the global call to promote green production and achieve sustainable development, the proper use of the digital economy plays an important role. The deepening development of the digital economy has led to changes in the input of manufacturing factors and the structure of product demand, which in turn has led to corresponding changes in the level of green and sustainable development. This study employs a factor input-output non-expectation SBM-DEM model to assess the green manufacturing efficiency of 273 prefecture-level and higher cities in China. The relationship between the digital economy and green manufacturing efficiency is analyzed based on this model. The rise of the digital economy is found to contribute to the increase in green manufacturing efficiency, albeit with a non-linear “inverted U-shaped” trend. At the same time, the current level of digital economy development is slowly improving but has not yet reached the inflection point of the “inverted U-shaped” curve, and digital economy development still has a positive impact on green manufacturing efficiency at the current level of development. Furthermore, government intervention is critical in moderating the inverted U-shaped link between the digital economy and green manufacturing efficiency, which has a major weakening effect.