Occurrence Of Disruption Research Articles

Flight, aircraft, and crew integrated recovery policies for airlines - A deep reinforcement learning approach

Airline schedules are easily affected by disruptions, leading to flight delays or (and) cancellations, causing significant financial losses to airline companies and inconvenience for passengers. When making recovery decisions, airlines need to simultaneously consider various entities, including flights, aircraft, and crew. This paper examines the integrated recovery policies for airlines to help re-schedule flights, re-route aircraft, and reassign crew members. To realize quick responses upon the occurrence of disruptions, an attention-based end-to-end deep reinforcement learning approach is proposed to learn a parameterized stochastic policy for the integrated airline recovery problem. Numerical experiments based on randomly generated disruption instances demonstrate that the proposed method outperforms the existing approaches and is applicable in realistic situations. The key insights obtained from our analyses are summarized as follows: (1) traditionally, among all disruption sources, it is most challenging and time-consuming to determine the recovery policies in reaction to aircraft delays and airport closures. However, the new approach developed in this study overcomes this difficulty and can provide high-quality recovery policies for aircraft delays and airport closures quickly. Thus, our work is especially valuable for airports and regions that suffer from frequent flight delays and closures, and can significantly improve their operational efficiency and service quality; (2) when traditional approaches are applied, the adoption of the well-known schedule robustness enhancement strategy ‘crew follow aircraft’ generally leads to high operations costs. Differently, our proposed approach can apply this strategy without encountering a significant cost growth. Therefore, airlines can fully leverage this strategy to gain additional advantages; (3) our developed new approach demonstrates high generality to accommodate various disruptions, which can benefit airlines and airports in the highly-volatile environment with various unpredictable events.

The influence of pregnant women's anxiety levels on fetal well-being and pregnancy complications: A cross-sectional study in Lombok, Indonesia

Pregnant women are a vulnerable group who are at risk of experiencing physiological changes that result in a partial decrease in immunity. Pregnancy with anxiety for pregnant women, which can affect maternal health, hinder development, cause emotional disturbances at birth, and even result in pregnancy complications. This type of research is observational-analytic with a cross-sectional design from January to June 2021. The population in this study is all third-trimester pregnant women at the Mataram City Regional Health Center and West Lombok Regency. There were 228 respondents in the study, taken using the accidental sampling technique. Data collection was carried out by accessing medical record data and filling out questionnaires for pregnant women who underwent examinations. The results of the chi square test showed that there was a relationship between anxiety and pregnancy complications with a p value of 0.0000 (p < 0.05) and a relationship between anxiety and fetal heart rate with a p value of 0.007 (p < 0.05). The ANOVA test results also showed that there was a simultaneous influence of fetal heart rate and pregnancy complications on anxiety in pregnant women, with a significance value of 0.0000 (p < 0.05) and an effect size of 74.6%. This research shows that early detection and management of anxiety during pregnancy is very necessary to prevent and minimize the occurrence of pregnancy complications and disruption of fetal well-being, which is characterized by an abnormal fetal heart rate.

Frekuensi Gangguan dan Energi Tak Tersalurkan Sebagai Indikator keandalan Sistem Jaringan Tegangan Menengah

The increasing need for electrical energy must be balanced with improved customer service. Customers will feel comfortable if they can enjoy an uninterrupted electricity supply in the form of a disconnection of the electricity supply for a certain period of time or what is commonly called the ENS (Energy Not Supplied) index and the AENS (Average Energy Not Supplied) index. The reliability of the electric power system is one of the things that is very important in order to maintain the performance of the three main pillars of PT. PLN (Persero). A reliable distribution network can be seen from the number of disruptions that often occur in the distribution network. Disruptions that arise in the distribution network arise due to internal factors such as less reliable distribution network components. In addition, it can also be caused by external factors such as natural disasters or the influence of trees and animals. Based on the results of the research that has been conducted, it is known that the occurrence of disruptions and the length of the duration of the disruption cause the Energy Not Supplied (ENS) value to increase as in April and July, the high duration of the blackout also makes the ENS higher, namely 792.857804 kW and 789.046811 kW. However, the distribution network at the Wagom feeder is still considered reliable in distributing electrical energy based on the SAIDI and SAIFI indices. From the research results, the SAIDI index at the Wagom feeder reached 8.96 hours/customer/year. While the SAIFI index at the Wagom feeder reached 2.08 times/customer/year.

Sewage Treatment Equipment Supply Chain Collaboration and Resilience Improvement Path Analysis: Collaborative Decision-Making, Information Sharing, Risk Management

Since the dawn of the 21st century, supply chains (SCs) have faced an array of unprecedented challenges, encompassing economic volatility, escalating geopolitical conflicts, intensified trade disputes, and persistent environmental degradation. These challenges have imposed immense pressures on SCs, amplifying both the risks and occurrences of disruptions. In response to these critical demands, there has been a substantial increase in academic, industrial, and governmental focus on the resilience and recovery capabilities of SCs. In this context, the supply chain (SC) for sewage treatment equipment has been significantly affected. This study aims to systematically investigate collaborative strategies and mechanisms for bolstering the resilience of manufacturing SCs within the sewage treatment sector, with particular attention to collaborative decision-making, information sharing, and risk mitigation throughout the SC lifecycle. Following a comparative analysis of various methodologies, this paper employed the structural equation model (SEM) and subsequently conducted a comprehensive survey of manufacturers specializing in glass fiber sewage treatment systems, yielding 385 valid responses. Through this data, a structural equation model was developed to analyze pathways for resilience enhancement. A thorough analysis of the results indicates that Supply Chain Collaboration (SCC) and collaborative decision-making are instrumental in strengthening Glass Fiber Sewage Treatment Supply Chain Resilience (SCR) through the implementation of effective information sharing and risk management practices. These findings contribute to the theoretical framework of SCC and SCR by clarifying the influence of collaborative practices while also providing practical guidance for the governance and strategic management of sewage treatment equipment enterprises and their associated SCs. The conclusions drawn from this study can guide us in establishing a more resilient and sustainable SC ecosystem, making it more directive and capable of mitigating complex disruptions.

Integrating human factors into the distribution model of goods and fast-moving consumer goods for effective inventory control

Multiple factors contribute to the occurrences of disruptions in workflow management within the e-commerce system that focuses on the distribution of goods and other fast-moving consumer goods (FMCG). These disruptions have particularly affected and increased lead times and caused frequent shipment delays. The causes of these disruptions, especially in the context of distribution of goods and FMCG towards inventory control, have been widely speculated upon in recent years. Given the recent interruptions, the study presented in this paper used a methodology called statistical model analysis (SMA) to study the impact of human factors (HFs) on the system performance in a warehouse distribution system. A case study was taken on a particular company called ABC and XYZ to model the impact of some specific HF such as job fatigue, and job rotation to name a few and to uncover the underlying reasons behind the ongoing disruptions within the distribution system. Specifically, the result of this study aims to provide a data-driven understanding of these issues and one of the contributions of this study is to enhance our understanding of the significance of these HFs, rather than focusing on the equipment and materials as seen in prior research. Through this data-based approach study, stakeholders in operations management, e-commerce, and the supply chain system would be well-informed in many ways to resolve the challenges faced by humans in the system towards enhancing their overall system performance.

Late gestation fetal hypothyroidism alters cell cycle regulation across multiple organ systems

BackgroundHypothyroidism is a common endocrine disruption observed in utero that adversely affects fetal growth and maturation leading to long-term impacts on health; however, the exact molecular mechanisms by which these deleterious effects occur are unknown. We hypothesize that fetal hypothyroidism during late gestation will disrupt cell cycle regulation in a tissue-specific manner. To evaluate this, eight pregnant gilts were dosed with either methimazole or an equivalent negative control during days 85–106 out of 114 days of gestation (n = 4/group). Following treatment, the gilts were humanely euthanized, and tissue samples of fetal heart, ileum, kidney, lung, liver, muscle, spleen, and thymus taken from two male and two female fetuses (n = 32) from each gilt.ResultsThe relative expression of three cell cycle promoters (CDK1, CDK2, and CDK4), and one cell cycle inhibitor (CDKN1A) was compared in each tissue to determine the effect of hypothyroidism on the developing fetus. All of the eight tissues examined experienced at least one significant up- or downregulation in the expression of the aforementioned genes as a result of treatment with methimazole. Substantial changes were observed in the liver and muscle, with the latter experiencing significant downregulations of CDK1, CDK2, and CDK4 as a result of treatment. In addition, all tissues were examined for changes in protein content, which further elucidated the impact of hypothyroidism on the fetal liver by the observation of a marked increase in protein content in the methimazole-treated group. Finally, the heart and liver were histologically examined for evidence of cellular hyperplasia and hypertrophy by measuring average nuclei density and size in each tissue, with the results showing a significant decrease in average nuclei size in the liver of hypothyroid fetuses.ConclusionsCollectively, these findings indicate the occurrence of organ-specific disruptions in cell cycle progression as a result of in utero hypothyroidism, which may explain the long term and widespread effects of hypothyroidism on fetal development.

DECAF cross-device characterization of tokamak disruptions indicated by abnormalities in plasma vertical position and current

Abnormal (deviating from the target) variations in the plasma vertical position Z and current Ip (such as vertical displacements, transient Ip ‘spikes’ and quenches) constitute common elements of a disruption, a phenomenon that is to be mitigated, or ultimately avoided in future reactor-relevant tokamaks. While these abnormalities are generally recognized cross-shot and cross-device, details in terms of appearance (or not) and order of these abnormalities in disruption event chains (DEC) are bound to the plasma state at the time of the chain initiation. Detection of these abnormalities is thus indicative not only of the onset of the plasma collapse itself but also of the disruption driving cause that is promoted at a particular plasma state. Here, the occurrence of disruptions, explored via the detection of an Ip quench, and the analysis of DEC constituted by Ip and Z abnormalities is reported for in total seven full device-year pairs of operation of three machines (4, 2 and 1 years of KSTAR, MAST-U and NSTX-U operation, respectively) using the DECAF code expanded tools and capabilities. It is shown that the disruption occurrence depends not only on the details of the plasma state but also on (device-dependent) technical elements of the shot exit scenario. Year-to-year changes in the main disruption causes and a reduction in the disruptivity rate, bound by device and operation upgrades, are reported. Particular trigger instances of DEC (and the full chains when applicable) are shown to occupy different parts of the operation space diagrams, in accordance with prior expectations. Plasma elongation is identified as an important factor influencing details of the chains and its role will be further explored.

Current Therapeutic Sequencing in Chronic Lymphocytic Leukemia.

The treatment landscape of chronic lymphocytic leukemia (CLL), the most frequent leukemia in adults, is constantly changing. CLL patients can be divided into three risk categories, based on their IGHV mutational status and the occurrence of TP53 disruption and/or complex karyotype. For the first-line treatment of low- and intermediate-risk CLL, both the BCL2 inhibitor venetoclax plus obinutuzumab and the second generation BTK inhibitors (BTKi), namely acalabrutinib and zanubrutinib, are valuable and effective options. Conversely, venetoclax-based fixed duration therapies have not shown remarkable results in high-risk CLL patients, while continuous treatment with acalabrutinib and zanubrutinib displayed favorable outcomes, similar to those obtained in TP53 wild-type patients. The development of acquired resistance to pathway inhibitors is still a clinical challenge, and the optimal treatment sequencing of relapsed/refractory CLL is not completely established. Covalent BTKi-refractory patients should be treated with venetoclax plus rituximab, whereas venetoclax-refractory CLL may be treated with second generation BTKi in the case of early relapse, while venetoclax plus rituximab might be used if late relapse has occurred. On these grounds, here we provide an overview of the current state-of-the-art therapeutic algorithms for treatment-naïve patients, as well as for relapsed/refractory disease.

INNOVATION MANAGEMENT MODEL TO IMPROVE CORPORATE INNOVATION PERFORMANCE

Entering the industrial era 4.0, technology continues to develop and is used to improve company performance. This emphasizes the occurrence of disruption between companies which is mainly driven using this technology. Previous studies have emphasized the importance of innovation to overcome this condition. Astra Group as one of the conglomerate groups in Indonesia has understood and implemented this consistently and persistently. For this reason, the innovation management model in this group is important to be investigated further to provide understanding and scientific contributions related to innovation management in corporations. From the literature, at least three important factors were found in the management of innovation, namely 1) managerial capabilities, 2) adhocracy culture, and 3) knowledge sharing on innovation capabilities and performance in this group. The findings may contribute to an opportunity for researchers to confirm this model in future research.

Exploring Small Medium Enterprise (SME) owners’ resources for resilience

Resilience can be defined as the aptitude to recover from unexpected events and sustain an acceptable level of competence. In contemporary times, it is irrefutable that every form of business and company must possess resilience. Some businesses, especially Small and Medium Enterprises (SMEs), are not as robust and will fold under pressure. Certain owners experienced failure due to their insufficient awareness, which hindered their ability to demonstrate resilience. Moreover, the insufficiency of financial resources and limited access to necessary assets significantly contribute to the ineffectiveness of business activities. This study aims to explore how the resources of SME owners add to the resilience of businesses. The most common sources of resilience amongst the owners appear to be a combination of adaptation and social support. Regarding owners’ adaptability, most business owners make efforts to adjust to the prevailing circumstances due to the occurrence of crises and disruptions in business operations. This study identified a range of social support mechanisms available to owners within diverse organizational structures. These mechanisms include support from individuals external to the company, social interactions with newly acquainted individuals, as well as internal and external relationships with individuals within the organization and potential collaborators if required. The study used purposive sampling, specifically targeting a limited sample size of five SME owners in Kedah. The structured interview serves as the primary method for collecting data. Subsequently, the textual data was transcribed to facilitate analysis through a coding procedure. Therefore, themes will be employed to link certain facts.

Analysis of the Use of Technology from the Perspective of Islamic Family Law in Era 4.0

Industrial revolution 4.0. causing a shift in lifestyle from a social, religious pattern to a materialistic and secular individual pattern. Apart from that, the cultural sector has been disrupted due to the development of social media which has reconstructed the cultural structure of society. Social relations between communities are now more closely established in the virtual world, so that relationships in the real world have become relative. This results in a lack of direct communication with family members because they focus on seeking their own pleasure. In the era of the industrial revolution 4.0, parents have also given gadgets to their children aged around 4-6 years. This research uses a social approach method and structural functionalism as its theory. The results of the research are that families do not reject revolution and use technology to help their daily lives. Apart from that, there are implications of structural functionalism theory with the occurrence of disruption in the era of the industrial revolution, especially in the social and cultural fields of society. The Industrial Revolution Era 4.0 is an era where various things in life are filled with sophisticated technology. Several families that the author studied have used technology produced by the industrial revolution 4.0. They use it in their daily lives so that it is felt as a need and urgency. As a result, there is a shift in perspective and lifestyle in society in various areas of life, one of which is social and cultural, resulting in disruption. The disruption process has gone through a process of externalization, objectification and internalization as per the theory of structural functionalism so that both are relevant.

SHIP DETECTION IN COSMO-SKYMED SAR IMAGERY USING A NOVEL CNN-BASED DETECTOR: A CASE STUDY FROM THE SUEZ CANAL

Abstract. The Suez Canal, strategically located as the shortest international sea route, plays a crucial role in facilitating the transportation of goods between Asia and Europe. However, the occurrence of traffic disruptions within the Canal poses a serious threat to global trade, as evidenced by the recent incident of the container ship Ever Given, which ran aground in the Suez Canal on March 23, 2021. This event led to a complete blockade of the Canal that lasted for six days, resulting in a fleet of ships waiting to pass through the Canal. This highlights the need to monitor the Canal to prevent similar disturbances in the future. In this paper, we propose a CNN-based attention-guided self-learning framework for ship detection from 3m high-resolution COSMO-SkyMed SAR imagery acquired in April 2021 via the Egyptian Suez Canal. We introduce a self-learning augmented segmentation (SLAS) technique to augment the dataset with new ship samples by pseudo-labeling an unlabeled dataset. We also present the Attention-guided Feature Refinement (AFR) module to extract more significant semantic features and contextual information, especially for ships of varying sizes in SAR images. Finally, the AFR module is fed into a Region Proposal Network (RPN) to generate a set of proposal anchors, which are later used in a Deep Detection Network (DDN) for ship classification and localization. Our experimental results demonstrate that the proposed method outperforms current state-of-the-art detection models in terms of detection accuracy, particularly in complex coastal scenes, with an overall accuracy of up to 87% mean average precision (mAP).

The risk of osteomyelitis after mandibular fracture is doubled in men versus women: analysis of 300,000 patients

Postoperative complications following mandibular fracture treatment vary from local wound infections to severe conditions including osteomyelitis and impaired fracture healing. Several risk factors have been associated with the development healing disorders, including fracture localisation, treatment modality and substance abuse. However, limited research on the sex-specific influence of these complications exists. A total of about 300,000 female and male patients with mandibular fractures were examined in two cohorts. After matching for confounders (age, nicotine and alcohol dependence, malnutrition, overweight, anaemia, diabetes, osteoporosis and vitamin D deficiency), two cohorts were compared with propensity-score-matched patients according to outcomes (osteomyelitis, pseudoarthrosis and disruption of the wound) within 1 year after fracture. There were significant differences between female and male patients regarding the occurrence of osteomyelitis (odds ratio [OR] [95% confidence interval]: 0.621 [0.563; 0.686]) and disruption of the wound (OR [95% confidence interval]: 0.703 [0.632; 0.782]). Surprisingly, matching for the expected confounders did not change the results substantially. Sex plays a dominant role in determining the risk stratification for postoperative osteomyelitis and disruption of the wound, after accounting for other potential confounding factors. Additional research is needed to understand the underlying mechanisms and to develop sex-specific strategies to prevent these complications.

Clinical validation of the nursing diagnosis risk for disturbed maternal-fetal dyad in high-risk pregnancy: A case-control study.

To obtain evidence of the clinical validity of the nursing diagnosis (ND) risk for disturbed maternal-fetal dyad in high-risk pregnancy. Causal validation of the ND through a case-control study performed in a university hospital with 155 high-risk pregnant women: 31 cases and 124 controls. A causal association was found between the ND etiological factors and the occurrence of disruption of the symbiotic maternal-fetal dyad; an association was verified when the etiological factor presented a p-value <0.05 and odds ratio >1. The risk factor absent-inadequate prenatal care; populations at risk, such as young-advanced maternal age and economically disadvantaged pregnant women; and association conditions, such as maternal conditions and compromised fetal oxygen transport, increased the outcome likelihood. The associated condition maternal illnesses appeared as a protective factor. Evidence of clinical validity of the ND risk for disturbed maternal-fetal dyad was obtained, and an association between etiological factors and disruption of the symbiotic maternal-fetal dyad was found. The results contribute to advance scientific knowledge in nursing teaching, research, and practice and support the nursing process in high-risk pregnancies.

The economic impact of water supply disruption from the Selangor River, Malaysia

Abstract The insidious economic impact of water disruption has received less attention compared to palpable climate disasters, but climate change and water security concerns call for investigation on cost consequences of property values and business losses in an already fragile water supply-demand balance in many developing countries. The economic impact of frequent water supply disruptions from the Selangor River in Malaysia due to technical issues, water pollution, and climate-related problems was estimated using the stock flow measure to assess property at risk, and survey to estimate business loss. The findings revealed that commercial, residential, and industrial property valued at RM459,041 million in 2020 in the State of Selangor and parts of Kuala Lumpur were at risk due to frequent water supply disruptions. A survey of small and medium enterprises from the manufacturing, construction, and services sectors revealed that 46% of the respondents were affected with losses amounting to RM2,053 million. The total economic impact of water supply disruption in 2020, combining both property value at risk and business loss, amounted to RM461,094 million, which accounted for 34% of Malaysia's GDP. A number of recommendations are made to prevent the widespread occurrence of water disruptions.

Optimization Models for the Vehicle Routing Problem under Disruptions

In this paper, we study the role of disruptions in the multi-period vehicle routing problem (VRP), which naturally arises in humanitarian logistics and military applications. We assume that at any time during the delivery phase, each vehicle could have chance to be disrupted. When a disruption happens, vehicles will be unable to continue their journeys and supplies will be unable to be delivered. We model the occurrence of disruption as a given probability and consider the multi-period expected delivery. Our objective is to either minimize the total travel cost or maximize the demand fulfillment, depending on the supply quantity. This problem is denoted as the multi-period vehicle routing problem with disruption (VRPMD). VRPMD does not deal with disruptions in real-time and is more focused on the long-term performance of a single routing plan. We first prove that the proposed VRPMD problems are NP-hard. We then present some analytical properties related to the optimal solutions to these problems. We show that Dror and Trudeau’s property does not apply in our problem setting. Nevertheless, a generalization of Dror and Trudeau’s property holds. Finally, we present efficient heuristic algorithms to solve these problems and show the effectiveness of the proposed models and algorithms through numerical studies.

ANALYSIS OF THE RELIABILITY OF ELECTRICAL DISTRIBUTION SYSTEMS USING THE TECHNICAL SECTION METHOD AND RNEA REPEAT GIBP-MESIR

The electricity distribution system can be said to be reliable if the process of delivering electricity to the customer does not experience significant interruptions. In the PT. PLN (Persero) ULP Duri found a variety of disturbances in one year. The resulting impact is, energy that is not channeled during the occurrence of disruption, thus making the reliability value on the electricity distribution system unreliable. The study aims to analyze the reliability of the system on the GIBP-MESIR repeat, using the Techniqeu Section Method and RNEA Method, as well as calculate the economic losses over a year. System reliability index results using Section Technique Method SAIFI 1,258 times/customer/year, SAIDI 5,324 hours/customer/year and CAIDI 4,232 hours/customer/year. The RNEA method SAIFI 1,844 times/customer/year, SAIDI 7,819 hours/customer/year, and CAIDI 4,239 hours/customer/year. For both methods the SAIFI, SAIDI, and CAIDI values are below SPLN 88-2 1986, then it can be said to be reliable. Economic fulfillment of Section Technique Method with ENS value 59.194.677,96kWh, AENS 3.453,39 kWh/customer, and Rp 85.518.551.248. RNEA method values ENS 86.933.685,93 kWh, AENS 5.071,681 kWh/customer, and Rp. 125.593.096.063 for one year.

Supply portfolio selection for lead-time sensitive manufacturers under operational and disruption risks

PurposeThis paper proposes a two-level supply chain including suppliers and manufacturers. The purpose of this paper is to design a resilient fuzzy risk-averse supply portfolio selection approach with lead-time sensitive manufacturers under partial and complete supply facility disruption in addition to the operational risk of imprecise demand to minimize the mean-risk costs. This problem is analyzed for a risk-averse decision maker, and the authors use the conditional value-at-risk (CVaR) as a risk measure, which has particular applications in financial engineering.Design/methodology/approachThe methodology of the current research includes two phases of conceptual model and mathematical model. In the conceptual model phase, a new supply portfolio selection problem is presented under disruption and operational risks for lead-time sensitive manufacturers and considers resilience strategies for risk-averse decision makers. In the mathematical model phase, the stages of risk-averse two-stage fuzzy-stochastic programming model are formulated according to the above conceptual model, which minimizes the mean-CVaR costs.FindingsIn this paper, several computational experiments were conducted with sensitivity analysis by GAMS (General algebraic modeling system) software to determine the efficiency and significance of the developed model. Results show that the sensitivity of manufacturers to the lead time as well as the occurrence of disruption and operational risks, significantly affect the structure of the supply portfolio selection; hence, manufacturers should be taken into account in the design of this problem.Originality/valueThe study proposes a new two-stage fuzzy-stochastic scenario-based mathematical programming model for the resilient supply portfolio selection for risk-averse decision-makers under disruption and operational risks. This model assumes that the manufacturers are sensitive to lead time, so the demand of manufacturers depends on the suppliers who provide them with services. To manage risks, this model also considers proactive (supplier fortification, pre-positioned emergency inventory) and reactive (revision of allocation decisions) resilience strategies.

Disruption-resilient supply chain entities with decentralized robust-stochastic capacity planning

This paper presents decentralized capacity planning models for four types of supply chain entities, classified based on functional similarities, to enhance their resilience. Novel resilience metrics are devised to quantify the proximity of backed-up, fortified, and recovered capacities to the amount of disrupted capacity by analyzing post-disruption events (i.e., absorption, adaptation, and restoration). Based on these metrics, bi-objective optimization models are developed to maximize resilience and cost-efficiency simultaneously to select proper business continuity plans contributing to supply chain entities’ proactive and reactive resilience. Finally, a robust-stochastic optimization method is tailored to address the uncertainties associated with the available time to recover and the impact and occurrence of disruptions. Also, disruption scenarios are simulated using a discrete-time Markov chain. Computational tests confirm the proposed models’ robustness, validity, and generality. The results describe essential features of business continuity plans, prescribe optimal decisions to enhance resilience, and predict how sensitive the resiliency and the imposed costs are to disruptions or proactive/reactive planning.

Revitalizing Indonesia's Print Media Competitive Strategy in the Digital Disruption Era:

The implementation of the Accurate, Solid, Speed, Smart, Innovative, Commitment ASSSIC (ASSSIC) management policy as an innovation of Jawa Pos Radar Jember (JPRJ) is a response to the occurrence of digital disruption; thus, JPRJ needs to create an adaptive management policy by strengthening the internal and external aspects of the company. The internal management policy is implemented through the application of ASSSICRJ as the Company's Management Information System (MIS), while the external aspect is addressed through ASSSIC Product by digitizing its media products. The purpose of this research is to analyze the competitive strategies employed by JPRJ in the era of digital disruption. The research method used is qualitative research with a case study approach on the implementation of ASSSIC, elaborated with Porter's Five Forces Analysis theory. The research findings conclude that the competitive strategies employed by JPRJ in the era of digital disruption are carried out through the ASSSIC management policy, which relies on the internal and external strengthening of JPRJ. The internal management policy, implemented through the application of ASSSICRJ as a vital MIS for JPRJ, enables the collection, management, analysis, and integration of data and information required for effective decision-making. On the other hand, the external management policy is implemented through the application of ASSSIC Product as JPRJ's convergence with the strengthening of digitalization in its media products, which is currently highly demanded by the majority of readers. This field finding has the potential to enhance Porter's Five Forces Analysis theory, which currently focuses only on external strengthening.