BSECompany Update12 Aug 2026 · 12 Aug 2026, 10:07 pm

Newspaper advertisement regarding financial results (Q-1 f.y. 2026-27)

Popular Estate Management Ltd · 531870

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Popular Estate Management Ltd has published its quarterly results for Q1 FY 2026-27 as per Regulation 33 of SEBI (Listing Obligations and Disclosure Requirements) Regulations 2015.

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Earnings Impact5/10
Growth Catalyst2/10
Governance Concern1/10
Regulatory Risk1/10
Balance Sheet Risk1/10
Liquidity Impact5/10
Market Sentiment5/10

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Popular Estate Management Ltd - 531870 - Announcement under Regulation 30 (LODR)-Newspaper Publication

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POPULAR ESTATE MANAGEMENT LIMITED Reg Office : F P No 35, NR.GEB Sb Staton, B/h Greenfield Bunglow, Prl Laboratory at Thaltej, Dascroi Nandigram, Thaltej, Ahmedabad. Tele : 079-26858881 Email : popularestatemanagement@yahoo.co.in CIN :L65910GJ1994PLC023287 Date: 12.08.2026 BSE LIMITED, Compliance Department, Phiroze Jeejeebhoy Towers, Dalal Street, Mumbai- 400001 SECURITY ID: POPULARES SECURITY CODE: 531870 SUB: INTIMATION REGARDING PUBLISHING QUARTERLY RESULTS AS PER REGULATION 33 OF SEBI (LISTING OBLIGATIONS AND DISCLOSURE REQUIREMENTS) REGULATIONS 2015. Dear Sir/Madam, With reference with the above subject, please find enclosed herewith the copy of newspaper advertisement published in Fress press in English language and lokmitra in Gujarati language dated 11th August,2026 regarding publishing of quarterly results as per Regulation 33, of SEBI (Listing Obligations and Disclosure Requirements), Regulations 2015. Please take the same on your record. Thanking you. Yours Faithfully, For Popular Estate Management Limited, Vikram Patel Director DIN: 00166707 11-08-2026 Tuesday Nepal’s real emergency isn’t Why employee behaviour may decide whether AI adoption deepens religious; it’s institutional Companies are investing than casual use. The paper conclusion. Rogers’ diffusion the same organisational billions in artificial intelligence. does not study employee model, Davis’s Technology permission to experiment. One They are purchasing AI tools, behaviour or organisational Acceptance Model, and the tries it a few times, receives rolling out training productivity, but it Unified Theory of Acceptance disappointing answers and programmes and introducing demonstrates that AI adoption and Use of Technology all returns to familiar methods. governance policies to varies substantially in depth argue that adoption depends The other treats those early encourage responsible use. and sophistication rather than on more than technical failures as part of the learning Progress is usually measured existing as a single, uniform capability. Perceived process. They refine their through familiar metrics: how phenomenon. usefulness, confidence, social prompts, verify AI outputs, many employees have access Using AI and using AI well influence and organisational discover new applications and to AI, how often they use it are not the same thing support consistently shape gradually integrate AI into and how many have That distinction exposes a whether people incorporate their daily work. This example completed training. These weakness in how many technologies do not spread I found Rogers’ work so new technologies into their is illustrative rather than a indicators reveal whether AI organisations evaluate their AI simply because they become relevant to today’s AI work. Technology succeeds finding from AI Premium, but has entered the workplace. strategies. They often assume available. Adoption depends revolution that I devoted an because people choose to use it reflects a behavioural They reveal far less about that widespread access and on how people perceive their entire chapter to it in my latest it meaningfully, not simply question that many whether it has become regular usage indicate relative advantage, whether book, Future of Work: AI because it is available. organisations have yet to embedded in how employees capability. Yet using AI the technology fits existing Augmented, Autonomous, Why do some employees examine systematically. think, solve problems and occasionally and integrating it work, whether they can Decentralised. Artificial move from trying AI to relying Technology alone is Nepal’s prime minister, Thursday, the unrest had make decisions. into everyday work are experiment with it safely and intelligence may represent a on it, while others stop after unlikely to provide the who had barely spoken in jumped provinces, and only A July 2026 working paper fundamentally different whether they observe others new technological wave, but the first few attempts? The complete answer. Curiosity, public since taking office in then did the prime minister from the National Bureau of behaviours. Consider two benefiting from its use. The it still enters organisations distinction becomes clearer at persistence, calibrated trust March, finally addressed the speak. Four days is not a long Economic Research NBER) & organisations. In one, most technology may be new, but through familiar human the level of individual and openness to nation after at least three time. but it is an eternity in a Yale Department of employees use AI to draft the behavioural mechanisms behaviours. The broader behaviour. Imagine two experimentation all influence people were killed in fast-moving communal Economics, AI Premium, by emails or summarise behind its adoption remain technology adoption literature employees receiving the same how people respond to communal violence that began dispute, where each hour of Nicola Borri, Aleh Tsyvinski and documents a few times each remarkably consistent. reaches much the same AI tool, the same training and unfamiliar tools. in Sunsari district and later official silence matters. Yukun Liu, offers an important week. In the other, fewer spread to the neighbouring Governments that respond clue. Drawing on roughly 380 employees use AI, but they Madhesh province. Prime quickly to flashpoints rarely trillion tokens of realised AI rely on it daily to analyse Minister Balendra Shah see them metastasise into consumption between January information, challenge appealed for patience, multi-district emergencies. 2024 and April 2026, the assumptions, redesign restraint and unity after people Governments that respond researchers examine how AI workflows and improve were killed in the violence, only once the toll has risen use is reflected in firms, decisions. Both organisations prompting authorities to invite the perception that markets and occupations. can report successful AI extend the curfew to new violence is what finally earns They find that the market- adoption. Their underlying areas. attention. implied AI premium is capability may be very A dispute over President Ramchandra strongest where AI different. This question has loudspeakers and religious Poudel spoke out before the consumption is associated been studied long before flags during a Hindu Prime Minister’s address to with frontier models, paid or artificial intelligence arrived. procession in Sunsari the nation. Opposition core users, seasoned users Everett Rogers' Diffusion of spiralled, within days, into lawmakers, including and longer prompts rather Innovations demonstrated that clashes that spread across members of the Nepali provincial lines into Siraha and Congress, raised the alarm in Dhanusha. This is not simply Parliament while the a story about Hindu-Muslim government remained quiet. tension. It is a story about a state that keeps discovering, too late, that it has no early- warning system for its own fault lines — and that keeps responding to crises with curfews rather than efficient prevention. Nepal’s recurring incidents of communal unrest are not primarily failures of tolerance between neighbours. They are failures of governance — of a state so consumed by its own political turnover that it has neglected the machinery of local mediation, timely policing, and visible accountability that keeps small disputes from becoming national emergencies. The violence in Sunsari began on a Sunday night. A curfew followed on Monday. By 11-08-2026 Tuesday ÷÷kkuuffrr{{ººkk,, 2 LLOOKKMMIITTRRAA …]Úðe rð¿kk™ {tºke zkì. SŒuLÿ ®‚nu ÷kuf‚¼k{kt ÷ur¾Œ sðkƒ{kt y÷ ™e™ku y™u Œu™e [ku{k‚k …h™e y‚h rðþu ‚{sqŒe yk…e RLV{uoþ™ ‚rðo‚e‚ (INCOIS) skufu y÷ ™e™ku yirŒnkr‚f heŒu ðkŒkðhýeÞ …rhrMÚkrŒyku™k (swell) ™e …rhrMÚkrŒyk{u k tVhu Vkhku ™k ŒksuŒh™k {qÕÞktf™ y™w‚kh {u Ëuþ™k fux÷kf ¼k„ku{kt ™ƒ¤k Wí¢ktrŒ …h ykÄkh hk¾þu, su{kt ™urð„uþ™, ykuVþkuh fk{„ehe y™u 2026 Ëhr{Þk™ rðfr‚Œ ÚkÞu÷e ¼khŒeÞ ‚{h {™‚q™ ðh‚kË ‚kÚku RrLzÞ™ ykuþ™ zkR…ku÷ y™u ËrhÞkfkt [Showing first 8,000 characters — download PDF for full document]